#best nlp libraries for javascript

[newaitechnology]

What Are the Best Free AI Tools for Developers in 2025?

In 2025, the rise of artificial intelligence continues to reshape how developers write, test, and deploy code. Whether you're building apps, creating AI models, or automating tasks, there’s a wide range of free AI tools for developers that can dramatically enhance your productivity. These tools are designed to reduce repetitive work, assist with code generation, and streamline your entire development workflow.

From intelligent code editors to open-source AI tools and cloud-based platforms, developers now have access to powerful solutions without needing to spend a dime. You’ll find tools that help with version control, documentation, real-time error detection, and even project planning—many of which are created and supported by thriving developer communities.

This guide covers a variety of free machine learning tools that allow you to train and deploy models easily, even if you’re just starting out. We’ll explore AI development platforms that simplify model building and deployment, along with tools that offer pre-built templates, automation workflows, and intelligent suggestions. Whether you're working in Python, JavaScript, or any other language, there’s something here for every developer.

You’ll also discover the best AI APIs free to integrate into your applications—from NLP and computer vision to sentiment analysis and chatbot development. Plus, we highlight some of the most popular free AI libraries for coders, which make it easy to add smart functionality to your apps without building everything from scratch.

No matter your experience level, these free tools can help you stay ahead in the fast-changing tech landscape. Dive into our expert-curated list of the best free AI tools for developers in 2025 and start building faster, smarter, and more efficiently with the power of AI.

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Summer Training for Engineering Students Program: Unlock Your Potential with Li-Mat Soft Solutions

What real-world machine learning projects can I showcase for internship applications?

To impress internship recruiters, showcase projects that demonstrate your understanding of real-world applications. Some good examples include:

Predictive Analytics: Build a model to predict sales, stock prices, or customer churn.

Image Recognition: Work on a project that uses deep learning for facial recognition or object detection.

Recommendation Systems: Create a movie, music, or product recommendation system using collaborative filtering.

Natural Language Processing (NLP): Build a chatbot or sentiment analysis tool.

These projects will showcase your ability to handle data, train models, and apply machine learning concepts.

How can a beginner prepare for a machine learning internship in just 1-2 months?

As a beginner, here’s a focused approach to prepare in 1-2 months:

Learn Python: It’s the foundation of machine learning, so mastering Python basics and libraries like Pandas, NumPy, and Matplotlib is essential.

Understand Core Concepts: Study key machine learning algorithms like Linear Regression, Logistic Regression, and Decision Trees.

Hands-On Practice: Implement small projects such as data analysis or simple predictive models using open datasets (Kaggle is a great resource).

Learn Libraries: Dive into Scikit-learn for building models and TensorFlow or Keras for deep learning.

By the end of the 1-2 months, you’ll have a solid foundation and a few practical projects to showcase.

Looking for the best Summer Training for Engineering Students program? Li-Mat Soft Solutions is the perfect provider! They offer industry-recognized training programs that blend theory with practical experience, ensuring you’re job-ready.

At Li-Mat Soft Solutions, students can enroll in courses like:

Machine Learning: From the basics to advanced algorithms, learn how to build predictive models and data analysis solutions.

Java Development: Master Java, from object-oriented principles to frameworks like Spring Boot and Hibernate.

Cyber Security: Understand the world of ethical hacking, network security, and digital forensics.

Web Development: Gain expertise in front-end and back-end technologies like HTML, CSS, JavaScript, React, Node.js, and more.

Their Summer Training for Engineering Students program is designed to provide hands-on learning, live project experience, and certifications that will give you a competitive edge in your career. Whether you're pursuing internships or job opportunities, this training will help you stand out in the competitive tech field.

Choose Li-Mat Soft Solutions and get the skills, knowledge, and experience needed to succeed in your future career.

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Text Processing Software Development

Text processing is one of the oldest and most essential domains in software development. From simple word counting to complex natural language processing (NLP), developers can build powerful tools that manipulate, analyze, and transform text data in countless ways.

What is Text Processing?

Text processing refers to the manipulation or analysis of text using software. It includes operations such as searching, editing, formatting, summarizing, converting, or interpreting text.

Common Use Cases

Spell checking and grammar correction

Search engines and keyword extraction

Text-to-speech and speech-to-text conversion

Chatbots and virtual assistants

Document formatting or generation

Sentiment analysis and opinion mining

Popular Programming Languages for Text Processing

Python: With libraries like NLTK, spaCy, and TextBlob

Java: Common in enterprise-level NLP solutions (Apache OpenNLP)

JavaScript: Useful for browser-based or real-time text manipulation

C++: High-performance processing for large datasets

Basic Python Example: Word Count

def word_count(text): words = text.split() return len(words) sample_text = "Text processing is powerful!" print("Word count:", word_count(sample_text))

Essential Libraries and Tools

NLTK: Natural Language Toolkit for tokenizing, parsing, and tagging text.

spaCy: Industrial-strength NLP for fast processing.

Regex (Regular Expressions): For pattern matching and text cleaning.

BeautifulSoup: For parsing HTML and extracting text.

Pandas: Great for handling structured text like CSV or tabular data.

Best Practices

Always clean and normalize text data before processing.

Use tokenization to split text into manageable units (words, sentences).

Handle encoding carefully, especially when dealing with multilingual data.

Structure your code modularly to support text pipelines.

Profile your code if working with large-scale datasets.

Advanced Topics

Named Entity Recognition (NER)

Topic Modeling (e.g., using LDA)

Machine Learning for Text Classification

Text Summarization and Translation

Optical Character Recognition (OCR)

Conclusion

Text processing is at the core of many modern software solutions. From basic parsing to complex machine learning, mastering this domain opens doors to a wide range of applications. Start simple, explore available tools, and take your first step toward developing intelligent text-driven software.

[slacourses]

Top Data Visualization Tools in 2025: Features & Comparison - Get Best Data Analyst Certification Course by SLA Consultants India

Data visualization plays a crucial role in transforming raw data into actionable insights, helping businesses make informed decisions. In 2025, several advanced data visualization tools are leading the industry, offering cutting-edge features that enhance data interpretation and storytelling. These tools are designed to handle complex datasets, provide real-time analytics, and integrate seamlessly with artificial intelligence for predictive analysis.

One of the most prominent tools in 2025 is Tableau, known for its interactive dashboards and user-friendly interface. Tableau allows users to create dynamic visualizations with drag-and-drop functionality, making it ideal for professionals who need to analyze vast amounts of data quickly. Data Analyst Course in Delhi

With AI-powered automation and natural language processing (NLP) capabilities, Tableau enables users to generate insights efficiently without extensive technical knowledge. Another powerful tool is Power BI by Microsoft, which stands out due to its deep integration with other Microsoft products. Power BI provides real-time reporting, AI-driven analytics, and seamless cloud connectivity, making it a preferred choice for businesses seeking enterprise-level solutions.

In addition to Tableau and Power BI, Google Looker is gaining traction as a leading cloud-based visualization tool. Looker offers advanced business intelligence capabilities and is optimized for big data analytics. Its ability to connect with multiple databases and cloud platforms makes it a robust choice for organizations that rely on real-time analytics. D3.js, an open-source JavaScript library, remains a top option for developers who require customized and interactive data visualizations. Unlike traditional BI tools, D3.js offers unparalleled flexibility, allowing users to create highly detailed, tailor-made visual representations of data. Data Analyst Training in Delhi

Another noteworthy tool is Qlik Sense, which provides associative data modeling, enabling users to explore and discover insights that might be overlooked in linear analysis. Its AI-powered assistance helps users uncover patterns and correlations, making data-driven decision-making more effective. Meanwhile, Python-based visualization libraries, such as Matplotlib, Seaborn, and Plotly, continue to be widely used by data scientists and analysts for their flexibility and compatibility with machine learning workflows.

Data Analyst Training Course Modules Module 1 - Basic and Advanced Excel With Dashboard and Excel Analytics Module 2 - VBA / Macros - Automation Reporting, User Form and Dashboard Module 3 - SQL and MS Access - Data Manipulation, Queries, Scripts and Server Connection - MIS and Data Analytics Module 4 - MS Power BI | Tableau Both BI & Data Visualization Module 5 - Free Python Data Science | Alteryx/ R Programing Module 6 - Python Data Science and Machine Learning - 100% Free in Offer - by IIT/NIT Alumni Trainer

With the growing importance of real-time analytics, Sisense has emerged as a top contender. Sisense offers an embedded analytics solution that allows businesses to integrate interactive dashboards into their applications seamlessly. Its ability to process large datasets efficiently makes it a strong choice for organizations that need real-time decision-making capabilities. Zoho Analytics is another tool gaining popularity due to its AI-powered insights and seamless integration with various business applications.

Enrolling in a Data Analyst Certification Course in Delhi is essential. SLA Consultants India offers a comprehensive training program that covers all the leading data visualization tools, including Tableau, Power BI, Python, and more. The course provides hands-on experience, real-world case studies, and expert mentorship, ensuring that students develop practical skills for a successful career in data analytics. With job-oriented training and placement assistance, this certification course equips aspiring data analysts with the knowledge and expertise needed to thrive in the competitive industry of 2025. Whether you are a beginner or an experienced professional, mastering these tools will open doors to high-paying career opportunities in data analytics. For more details Call: +91-8700575874 or Email: hr@slaconsultantsindia.com

[enterprisewired]

10 Best Programming Languages for AI

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Artificial Intelligence (AI) is reshaping industries, driving automation, and revolutionizing the way we interact with technology. Whether you’re developing machine learning models, creating neural networks, or working on natural language processing (NLP), choosing the right programming language is essential. But with so many options available, which ones stand out?

Here, we’ll explore the best programming languages for AI, their strengths, and how they contribute to AI development.

10 Programming Languages for AI: Strengths and Contributions

1. Python

Python is the undisputed leader in AI development. It’s widely used for machine learning, deep learning, and data science, thanks to its simplicity and extensive library support. Frameworks like TensorFlow, PyTorch, and Scikit-learn make Python the go-to choice for AI engineers.

What is Python used for in AI?

Python is used for building machine learning models, automating tasks, and creating AI-driven applications such as chatbots, recommendation systems, and image recognition software.

2. R

R is a powerful language for statistical computing and data visualization. It’s commonly used in AI projects that require deep statistical analysis. Libraries like caret and randomForest support AI model development.

What is R used for in AI?

R is primarily used for analyzing large datasets, performing statistical modeling, and implementing machine learning algorithms for research and development.

Also Read: In-Demand Programming Languages: A Comprehensive Guide

3. Java

Java’s versatility and scalability make it a strong choice for AI development, particularly in enterprise applications. It’s often used in AI-powered chatbots, fraud detection systems, and cybersecurity applications.

What is Java used for in AI?

Java is used for building large-scale AI systems, integrating AI into business applications, and handling complex AI-driven processes.

4. C++

C++ is known for its speed and efficiency, making it suitable for AI applications requiring high-performance computing, such as gaming AI and real-time decision-making systems.

What is C++ used for in AI?

C++ is widely used for developing AI in robotics, autonomous systems, and high-speed AI-driven simulations.

5. Julia

Julia is a rising star in AI and machine learning. Its high-performance computing capabilities make it ideal for handling massive datasets and complex numerical computations.

What is Julia used for in AI?

Julia is used for high-performance machine learning applications, scientific computing, and mathematical modeling in AI research.

Also Read: Tech Pay Guide: 9 Key Factors That Influence Developer Salaries

6. Lisp

Lisp is one of the oldest programming languages for AI and is still relevant today due to its flexibility and symbolic processing capabilities. It’s often used in NLP and AI-driven expert systems.

What is Lisp used for in AI?

Lisp is used for developing AI algorithms, processing symbolic data, and building intelligent agents for automation.

7. Prolog

Prolog is a logic-based AI language that excels in problem-solving and knowledge representation. It’s widely used in AI research and applications like expert systems and automated reasoning.

What is Prolog used for in AI?

Prolog is used for developing AI-based reasoning systems, chatbots, and rule-based AI applications.

8. JavaScript

JavaScript plays a growing role in AI development, especially for web-based AI applications. Frameworks like TensorFlow.js allow developers to run machine learning models directly in the browser.

What is JavaScript used for in AI?

JavaScript is used for developing AI-powered web applications, real-time data visualization, and interactive AI-driven tools.

9. Scala

Scala, known for its functional programming capabilities, is gaining popularity in AI and big data analytics. It’s often used with Apache Spark for handling massive datasets.

What is Scala used for in AI?

Scala is used for processing large-scale AI data, implementing machine learning models, and integrating AI into big data platforms.

Also Read: Mobile App Developers: Driving Innovation in the Digital Age

10. Swift

Swift, Apple’s preferred programming language, is becoming more relevant in AI for mobile applications. It’s used in AI-powered iOS apps, including voice recognition and image processing tools.

What is Swift used for in AI?

Swift is used for developing AI-powered mobile applications, integrating AI into iOS apps, and processing machine learning models on Apple devices.

[aljaishsociety]

Software Development With AI Code Generator

In today’s fast-evolving tech landscape, AI code generators have emerged as transformative tools for developers and businesses. Leveraging artificial intelligence, these tools simplify software development by automating code creation, drastically reducing the time and effort required to build complex programs. As AI-driven tools grow across various sectors, AI code generation promises to drive innovation at unprecedented speeds.

What is an AI Code Generator?

An AI code generator uses machine learning algorithms to write, improve, and refactor code automatically. By understanding natural language or simplified programming instructions, these tools convert inputs into executable code, enabling both developers and non-programmers to build applications and automate workflows. AI code generators rely on natural language processing (NLP) and machine learning (ML) to “understand” tasks and produce relevant code.

Code Generation

Following model processing, the AI moves to the code generation phase. At this point, the tool creates the actual code based on the task interpretation. Many AI code generators are versatile, capable of producing code in multiple languages like Python, JavaScript, or C++. This adaptability allows users to select their preferred language, making project integration easier.

Refinement

After the initial code generation, users typically enter the refinement stage. Here, they provide feedback or additional instructions to fine-tune the AI-generated code. The AI then modifies the code to better align with the user’s specific needs. This iterative process improves the final output, ensuring it closely meets the user’s requirements.

Input Processing

The AI code generation process begins with input processing, where the user describes a programming task in natural language. For instance, a user might request the AI to "create a function to sort an array." The AI interprets this instruction, translating it into a structured programming task. This initial step is crucial, as it shapes the entire code generation process.

Model Processing

Once the AI has processed the user’s request, it enters the model processing stage. Here, the AI uses its training data to analyze the request and determine the optimal approach. It identifies the necessary syntax, libraries, and structures relevant to the task. Drawing on its extensive knowledge, the AI generates code that aligns with best practices in software development.

Benefits of AI Code Generators

AI code generators are transforming the way software is written, offering several advantages to developers and businesses alike.

Faster Development

AI code generators excel at quickly producing code, particularly for repetitive tasks or standard code patterns. In seconds, these tools can generate functional code, significantly streamlining the coding process and saving developers substantial time. This acceleration can reduce development cycles from hours or days to just minutes, allowing teams to allocate more time to critical and complex aspects of their projects.

Reduced Errors

Trained on large datasets of best practices and established coding patterns, AI code generator often produce cleaner and more efficient code than manual efforts alone. This training reduces the likelihood of human errors and results in more reliable, robust software with fewer bugs. Improved code quality leads to smoother workflows and better overall project outcomes.

Enhanced Productivity

By automating routine coding tasks, AI code generators enable developers to focus on high-level tasks requiring critical thinking, such as system architecture and algorithm design. This allows teams to work more efficiently, speeding up project timelines and improving overall output. Enhanced productivity also fosters innovation, as developers have more time to tackle challenging problems.

Learning and Knowledge Sharing

AI code generators provide a valuable learning resource for newer developers, offering hands-on insights into proper syntax, coding conventions, and efficient use of functions and libraries. Reviewing AI-generated code helps novice programmers understand core programming concepts, while experienced developers can support team knowledge-sharing by helping interpret and utilize the generated code effectively.

Cross-Language Code Generation

One of the major advantages of AI code generators is their ability to support multiple programming languages. This capability allows developers to generate code in languages they may be less familiar with, broadening their skill set and reducing the learning curve associated with new languages. This flexibility enhances team adaptability, making them more competitive across a diverse tech landscape.

Common Use Cases of AI Code Generators

AI code generators are widely used across various industries and development tasks. Here are some common applications.

Automated Test Generation

AI tools can swiftly generate unit and integration tests by analyzing the existing codebase, ensuring comprehensive testing without requiring developers to manually write all test cases. This automation allows teams to achieve greater test coverage, ultimately enhancing software quality. It saves time and enables developers to concentrate on more critical tasks, confident that testing is being conducted efficiently.

Code Refactoring

To maintain code quality over time, AI coding tools for seasoned coders play a significant role in the refactoring process. By identifying inefficiencies in the existing code, these tools can recommend improvements that boost both performance and readability. This accelerates and standardizes the refactoring process, alleviating the workload for developers. With AI assistance, teams can keep their code clean and maintainable, which is essential for the long-term success of projects.

Frontend Development

AI code generators are crucial in frontend development, as they can automatically create UI components for web and mobile applications. Developers need only input design specifications or mockups, and the tools will generate the necessary HTML, CSS, and JavaScript code. This accelerates development and helps maintain design consistency across applications, allowing teams to bring their products to market faster while ensuring a polished user interface.

Database Management

In database management, AI code generators simplify tasks by automatically creating SQL queries, database schemas, and scripts. This feature is particularly useful for non-technical users who need to work with databases but lack extensive programming skills. By streamlining these processes, AI enables users to manage data effectively without deep technical expertise, empowering a wider range of team members to engage in data-related tasks.

API Integration

Integrating multiple APIs into a system can often be labor-intensive and time-consuming for developers. AI code generators can alleviate this burden by automatically generating code for API requests, parsing responses, and managing errors. This reduces the manual coding effort involved in API integration, allowing developers to focus on more strategic project elements. By automating these repetitive tasks, teams can improve efficiency and deliver more robust applications in less time.

FAQs

Can AI code generators replace human developers?

No, AI code generators are tools designed to assist developers, not replace them. While they can automate repetitive tasks, human oversight is necessary for problem-solving, creativity, and ensuring code quality.

Are AI code generators safe to use?

Generally, yes, but like any tool, the code they generate should be reviewed for security vulnerabilities. AI can overlook edge cases or introduce bugs, so human developers should always validate the output.

What programming languages do AI code generators support?

Most AI code generators support a wide range of languages, including Python, JavaScript, Java, C++, and more. However, the level of proficiency may vary across different languages.

Do AI code generators help with debugging?

Some AI tools offer features that assist in debugging by suggesting fixes or identifying likely error sources. However, the debugging process still requires a strong understanding of the codebase.

Conclusion

AI code generators are becoming indispensable tools in modern software development, offering efficiency, speed, and assistance in managing routine tasks. While they come with limitations—especially when dealing with complex or highly customized projects—they are undeniably a powerful asset for developers of all skill levels. By automating tedious coding processes, these tools free up time for more creative and strategic work, ultimately accelerating the development cycle.

[mitcenter]

Beyond Bar Charts: Exploring the Best Data Visualization Tools of 2024

In the ever-evolving world of data visualization, the year 2024 brings a host of new and improved tools that go far beyond the classic bar chart. Whether you're a data scientist, business analyst, or a curious enthusiast, having the right tools to visualize data can make a significant difference in how insights are derived and communicated. This blog explores some of the best data visualization tools of 2024 that promise to elevate your data storytelling to new heights.

1. Tableau: The Gold Standard

Tableau remains a powerhouse in the data visualization landscape. Known for its user-friendly interface and robust capabilities, Tableau allows users to create interactive and shareable dashboards. In 2024, Tableau continues to impress with enhanced features such as AI-driven insights and natural language processing (NLP). These advancements make it easier for users to ask questions and receive visual answers without deep technical know-how.

Tableau's integration with various data sources, from spreadsheets to cloud databases, ensures that it remains a versatile choice for organizations of all sizes. Its community and extensive library of resources also provide ample support for users looking to master the tool.

2. Power BI: Microsoft's Heavyweight

Power BI by Microsoft continues to be a favorite among businesses due to its seamless integration with other Microsoft products like Excel and Azure. The 2024 updates to Power BI include improved real-time analytics capabilities and enhanced AI features. These updates allow users to automate data preparation and uncover insights faster than ever before.

Power BI's strength lies in its ability to handle large datasets and provide detailed analytics, making it ideal for enterprises looking to make data-driven decisions. Its collaborative features enable teams to work together efficiently, sharing insights and dashboards across the organization.

3. D3.js: The Developer's Choice

For those who prefer a more hands-on approach, D3.js remains a top choice. This JavaScript library allows developers to create highly customized and interactive data visualizations. The flexibility of D3.js is unmatched, making it the go-to tool for those who need precise control over their visualizations.

In 2024, D3.js continues to evolve with new plugins and community-driven enhancements that simplify the development process. While it has a steeper learning curve compared to other tools, the level of customization and the quality of visualizations that can be achieved are well worth the effort.

4. Google Data Studio: The Accessible Option

Google Data Studio is an excellent option for those who need a free, web-based tool that integrates well with other Google services. In 2024, Google Data Studio has introduced new templates and connectors, making it easier for users to create and share reports.

One of the standout features of Google Data Studio is its ability to pull data from multiple sources, including Google Analytics, Google Ads, and BigQuery. This makes it a valuable tool for marketers and analysts who rely on Google’s ecosystem for their data needs.

5. Looker: The Modern BI Platform

Acquired by Google, Looker has solidified its position as a leading business intelligence (BI) and data visualization platform. Looker’s strength lies in its ability to model data directly from databases, providing real-time insights without the need for data extraction.

In 2024, Looker has expanded its capabilities with new integrations and enhanced data governance features. This ensures that organizations can maintain data accuracy and security while empowering users to create their own dashboards and reports.

6. Qlik Sense: Associative Data Engine

Qlik Sense sets itself apart with its associative data engine, allowing users to explore data in a non-linear fashion. This unique approach enables users to discover hidden insights by freely navigating through their data.

The 2024 updates to Qlik Sense include enhanced AI and machine learning capabilities, making it easier for users to uncover patterns and trends. Its robust data integration and preparation tools also ensure that users can work with diverse datasets seamlessly.

7. Chartio: The Collaborative Tool

Chartio, recently acquired by Atlassian, has made significant strides in becoming a more collaborative and user-friendly data visualization tool. With a focus on simplicity and collaboration, Chartio allows teams to create and share interactive dashboards effortlessly.

In 2024, Chartio introduces new features that enhance its collaborative capabilities, such as improved version control and integration with other Atlassian products like Jira and Confluence. This makes it a valuable tool for teams that need to work together on data projects.

Conclusion

As data becomes increasingly integral to decision-making processes, the tools we use to visualize and interpret that data must keep pace. The best data visualization tools of 2024 offer a range of features and capabilities that cater to different needs and skill levels. Whether you need the user-friendly interface of Tableau, the deep integration of Power BI, the customization of D3.js, or the accessibility of Google Data Studio, there’s a tool out there to help you turn data into actionable insights.

Exploring these tools and understanding their unique strengths will empower you to tell more compelling data stories and make more informed decisions in the year ahead. Beyond bar charts, the future of data visualization is bright, dynamic, and incredibly exciting.

[nautiyal-tech]

The Future of Web Development in India: Trends, Insights, and Opportunities

The web development industry in India has witnessed exponential growth over the past decade. This vibrant sector has been pivotal in driving the country's digital transformation and fostering economic growth. With a burgeoning startup ecosystem, an increasing number of tech-savvy professionals, and supportive government policies, India is poised to become a global hub for web development. As we look to the future, it's crucial to understand the emerging trends, in-demand skills, and the challenges and opportunities that lie ahead for web developers in India.

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Evolving Technologies

The landscape of web development is continuously evolving, influenced by rapid technological advancements. Some of the key technologies shaping the future of web development in India include:

1. Artificial Intelligence (AI) and Machine Learning (ML)

AI and ML are revolutionizing web development by enabling more personalized and interactive user experiences. From chatbots and virtual assistants to predictive analytics and recommendation engines, AI and ML are becoming integral components of modern web applications.

2. Progressive Web Apps (PWAs)

PWAs are gaining popularity due to their ability to deliver a native app-like experience on the web. They offer fast loading times, offline capabilities, and improved performance, making them an attractive option for businesses looking to enhance their digital presence.

3. Blockchain Technology

Blockchain is set to transform web development by introducing decentralized applications (dApps) that offer enhanced security, transparency, and immutability. This technology is particularly relevant for industries such as finance, healthcare, and supply chain management.

4. Voice Search and Natural Language Processing (NLP)

With the rise of voice-activated devices and virtual assistants, optimizing websites for voice search is becoming increasingly important. NLP algorithms are enabling more accurate and intuitive voice interactions, making it essential for web developers to adapt to this trend.

5. WebAssembly

WebAssembly is a game-changer for web development, allowing developers to run high-performance code on web browsers. It enables the execution of complex applications, such as games and video editing tools, directly within the browser, bridging the gap between web and native applications.

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Skill Trends

As the web development industry evolves, so do the skills required to stay competitive in the Indian market. Here are some in-demand skills for web developers in India:

1. JavaScript Frameworks and Libraries

Proficiency in JavaScript frameworks and libraries, such as React, Angular, and Vue.js, is crucial for modern web development. These tools enable developers to build dynamic and responsive web applications with ease.

2. Full-Stack Development

Full-stack developers, who possess expertise in both front-end and back-end development, are highly sought after in the Indian market. Familiarity with technologies like Node.js, Express.js, and databases such as MongoDB and SQL is essential for full-stack development.

3. DevOps and Automation

DevOps practices and automation tools, such as Docker, Kubernetes, and Jenkins, are becoming increasingly important for streamlining the development and deployment process. Knowledge of these tools can significantly enhance a developer's productivity and efficiency.

4. Cybersecurity

With the growing threat of cyberattacks, cybersecurity has become a critical skill for web developers. Understanding secure coding practices, encryption techniques, and vulnerability assessments is essential for building robust and secure web applications.

5. UX/UI Design

A strong grasp of UX/UI design principles is vital for creating user-friendly and visually appealing websites. Skills in wireframing, prototyping, and tools like Adobe XD and Sketch can give developers an edge in the competitive market.

Industry Insights

To gain a deeper understanding of the future landscape of web development in India, we reached out to industry leaders for their insights:

Expert Perspective:

"India's web development industry is at the cusp of a major transformation. With the increasing adoption of AI, blockchain, and other cutting-edge technologies, the demand for skilled web developers is set to soar. It's crucial for developers to continuously upskill and stay abreast of the latest trends to remain relevant in this dynamic field."

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Challenges and Opportunities

Challenges

While the future of web development in India looks promising, developers face several challenges:

Skill Gap: The rapid pace of technological advancements has created a skill gap, with many developers struggling to keep up with the latest tools and frameworks.

Cybersecurity Threats: As cyber threats become more sophisticated, ensuring the security of web applications is a significant challenge.

Infrastructure: In some regions, inadequate infrastructure and internet connectivity can hinder the development and deployment of web applications.

Regulatory Compliance: Navigating the complex landscape of data privacy and regulatory compliance can be challenging for developers.

Opportunities

Despite these challenges, there are numerous opportunities for web developers in India:

Growing Demand: The increasing demand for digital transformation across various industries is driving the need for skilled web developers.

Startup Ecosystem: India's vibrant startup ecosystem offers ample opportunities for web developers to work on innovative projects and grow their careers.

Global Projects: Indian web developers have the opportunity to work on global projects, thanks to the rise of remote work and freelancing platforms.

Government Initiatives: Government initiatives such as Digital India and Startup India provide support and resources for web developers to thrive.

The Role of India in Global Web Development

India is rapidly emerging as a key player in the global web development landscape. With a large pool of talented developers, competitive pricing, and a strong emphasis on innovation, India is becoming a preferred destination for web development outsourcing. Additionally, Indian developers are increasingly contributing to open-source projects and global tech communities, further solidifying the country's position on the global stage.

Conclusion

The future of web development in India is bright, with immense potential for growth and innovation. By embracing emerging technologies, upskilling, and leveraging the opportunities available, Indian web developers can play a pivotal role in shaping the digital landscape. As we look ahead, it's clear that India is well-positioned to become a global leader in web development.

If you're a web developer looking to stay ahead in this dynamic field, now is the time to invest in continuous learning and skill development. Engage with industry leaders, participate in tech communities, and stay updated on the latest trends to ensure you remain competitive.

We encourage you to share your thoughts on the future of web development in India in the comments below. Let's start a conversation and learn from each other's experiences. Don't forget to like and share this post to help others in our community stay informed and inspired.

[ranjitha78]

A Look Behind the Scenes: My Developer Toolbox's Technologies

My "career" as a virtual assistant driven by cutting-edge technology consists of answering questions and processing data. I may not have the same conventional professional path as human developers, but I can provide you with insight into the technologies that enable me to help you efficiently.

Choosing the top full-stack developer institute can further accelerate your journey into this thriving industry.

Back-End Technologies:

Python: The Brains Behind the Scenes

The programming language that powers my functionality is called Python. It is readable, flexible, and enables the smooth integration of different parts. Python manages intricate data processing and logic operations, enhancing user interactions.

SQL and NoSQL Databases: Safe Knowledge Storage

Information is stored and managed in databases using NoSQL and Structured Query Language (SQL). NoSQL databases provide a variety of data types, whereas SQL databases arrange data in organized tables. This guarantees easy access to pertinent information during talks.

Machine Learning Libraries: Adding a Touch of Intelligence

Libraries like TensorFlow and PyTorch enable me to understand context, recognize patterns, and provide more nuanced responses over time. Machine learning algorithms help me adapt and improve based on the interactions I have with users. Choosing the best full-stack developer courses in Hyderabad is a crucial step in acquiring the necessary expertise for a successful career in the evolving landscape of full-stack developers.

Technologies at the front end:

HTML: Laying the Groundwork

HTML, or Hypertext Markup Language, is used to organize content on websites. It offers the framework for information display, enabling me to give answers in an understandable manner.

CSS: Visual Appeal Styling:

Cascading Style Sheets (CSS) improve how information is presented visually. It assists me in applying layouts, colors, and styles to make the user experience both aesthetically beautiful and user-friendly.

JavaScript: Enabling Dynamic Interactions

JavaScript makes our conversations more interactive. It enables me to react to user inputs in real time, resulting in an encounter that is more dynamic and interesting.

Layer of Communication:

APIs: Filling the Void

I may get real-time information and interact with external services thanks to application programming interfaces (APIs). They serve as links between other systems, broadening my access to knowledge.

NLP: Natural Language Processing: Interpreting Your Spoken Words

My ability to understand and react to natural language is enhanced by NLP algorithms. Thanks to technology, I can comprehend the subtleties of your questions and provide responses that are appropriate for the given environment.

Even though I don't work in a traditional sense, these technologies coexist peacefully to enhance our interactions. Every component that goes into producing a smooth and clever conversational experience, from the front-end technologies that present information in an approachable way to the back-end logic that handles data, is essential.

If you want to learn more about full-stack developers, I highly recommend the Full Stack Developer course in Hyderabad because they offer certifications and job placement opportunities. Experienced teachers can help you learn better. You can find these services both online and offline. Take things step by step and consider enrolling in a course if you’re interested.

I hope I answered your question successfully. If not, feel free to mention it in the comments area. I believe I still have much to learn. Thank you for spending your valuable time and upvotes here. Have a great day.

[quadrishinnovation]

5 Web Development Trends that Will Rule the Year of 2022 and Beyond

If you have been in the IT sector for a while, then you must be acquainted with how fast web development is evolving. New and advanced technologies along with better work processes are constantly being introduced in the market.

While this positively impacts the overall industry, businesses sometimes find it a little tough to keep up with the latest trends.

However, for businesses to stay in demand and ahead of the competition, they must practice new methodologies and put the effort in.

Besides that, identifying the right web development trends also becomes quite challenging for businesses. But don’t worry!

Below is the guide that accumulates the top web development trends that will help you to choose the right trend for your company:

Progressive Web Apps (PWA)

Progressive Web Apps have been around for some time now and will continue to stay around because of their native app-like user experience. Seamless installations, smooth updating and maintenance, and more flexible distribution are some of PWA’s advancements for businesses.

PWAs can be a huge advantage to your company by improving customer engagement and revenue in the future.

AI Chatbots

Do you know that, in a survey, AI chatbots have seen a 136% upsurge in the adoption rate and are believed to be significantly leveraged by more businesses as well? AI Chatbots is an emerging technology that runs on Natural Language Processing (NLP) and interacts with users via text, speeches, and graphics.

AI Chatbots streamlines interaction processes with users and is one of the reasons why more and more companies are leveraging them. Personalization, 24x7 support, increased customer support are some of the benefits it comes with.

JavaScript Frameworks

JavaScript Frameworks or JavaScript libraries are the pre-written JavaScript codes that help users develop JavaScript-based applications effortlessly. JavaScript libraries are the most preferred way while developing any application because they help users develop efficient code that is easy to process.

This developer-friendly language is one of the best web development trends and will continue to follow the same in the coming years, too.

Voice Search Technology

Along with the other trends, voice search technology has also experienced an upsurge after the pandemic. In fact, in a survey, it was found that 91% of the brands have already invested in the technology in some ways. Crazy, right!

Voice search technology offers a bunch of advantages such as hassle-free searching, quick access to the information, making multi-tasking easy, increased customer interaction, and more.

Serverless Architecture

As the name says, the serverless architecture allows to build and manage applications without having to manage infrastructure. It cuts out the processes like provision, scaling, and maintaining servers to run the database and storage devices.

Here are some of the other benefits of serverless architecture that makes it one of the top web development trends in 2021 and beyond:

●     Event-based architecture

●     Reduced architecture costs

●     Faster deployments

●     Greater flexibility

Conclusion

It is pretty evident that web development is on-demand and is experiencing a serious upsurge in the industry. While its trends constantly evolve, businesses must identify the right trends in order to maximize their business and profitability.

The above guide will follow you through some of the best web development trends in 2022 and beyond.

[holytheoristtastemaker]

Artificial Intelligence is the use of computers or machines that have been created to work and react like humans. Some of the computers that have AI, are designed to include speech recognition, and learn user behaviours so they can predict activities or decisions before they happen.

AI creates a bridge to a new kind of interface, making work processes easier for businesses and customers alike.

Why Is AI Important?

There are constant AI technological advances being made, so why not make the most of them and start integrating them into your toolset today? Read on to find out just why AI is important and how you can benefit from it in your work too.

Lower Costs

By integrating Artificial Intelligence into your toolset, you can stand to both save and earn more money. AI will leave you spending less time on various aspects of website management and development, freeing some of your time up and allowing you to finish websites faster. It will also leverage your set of skills and allow you to build greater sites that people will be willing to pay more money for.

Improve Customer Experience

Artificial Intelligence can be used to analyse data in much more depth than the human eye, so will greatly improve the customer experience. It will allow a more personalised and streamlined experience that users will be grateful for. By integrating AI into your toolset, you will soon learn about certain trends and patterns that AI picks up and utilise this with future sites you build, as well as being able to make suggestions to improve the customer journey on the site.

It’s The Future

With so many devices in our everyday lives tuning in to AI, it’s important websites are no different. Just look around many homes and you will likely see a device such as Amazon’s Alexa or Google Home. Phone’s have Siri or Bixby and many laptops have AI systems such as Cortana. As our technology continues to develop, websites need to do this too. Soon we will expect everything to be integrated and be able to control websites in a similar way to our AI devices with voice control and recognition.

How To Integrate AI Into Your Toolset

Chat Bots

One popular example of AI that is integrated into many different websites now, is the chat bot. A feature on a number of major sites, chat bots allow customers to ask and receive answers to questions without an employee having to take time out of their day to answer menial questions that they get asked all the time. The use of AI cuts out the middleman and recognises certain phrases and words to give the most relevant and comprehensive answer.

The first chatbots used to rely on simple, pre-programmed conversational pathways, but these had disappointing and often irrelevant results. More recently they use sophisticated natural language processing (NLP) systems which are a lot more complex and don’t follow just a scripted path, but allow for more meaningful conversations.

Sketch to Code

If you’ve just started in web design, or there are certain elements you are still learning about, AI can help with “sketch to code”. This clever piece of AI can transform a handwritten note, sketch or diagram into a valid HTML mark-up code that maintains itself. This can work from something as simple as a new design for a quote system, to something more complex.

Background Systems

AI can work in the background of a site in the run up to events and collect key aspects such as website analytics. Once this data is complete, the AI can take final instructions from you such as the content, theme and color preference and create a design from scratch that it thinks will perform the best due to the intelligence and knowledge it has been gathering in the background.

Voice Recognition

Back in 2012, the W3C Community introduced the Web Speech API specification with the aim of enabling speech recognition and synthesis in modern browsers. At present, Google Chrome is the only browser that has introduced this, however there is a HTML5 Speech Recognition API will allows JavaScript to have access to a browser’s audio stream and to convert it into text.

It’s important to get up to speed with voice recognition API’s as it’s predicted voice control will be huge in the future. If populating websites, think about how people speak and be sure to include some long-tail keywords that sound more natural. This will help those sites to rank when voice control is adopted more widely.

Adobe Sensei

Adobe Sensei is an AI and machine learning framework that is powering Adobe tools. It is a handy option to add to your toolkit to manage and work on your files.

If you are sourcing images for a website in Adobe Stock, there are over 100 million assets to sift through. Adobe Sensei uses AI and deep learning to understand what exact objects are within an image as well as deeper components such as the aesthetic quality, composition, color palette and even the emotional concept behind the images. This means it can quickly find the image most matched to your needs, saving you hours of time you would have spent sorting through to find the image you want.

Yossarian

Yossarian is a great tool that allows you to craft mood boards. With an aim to generate new ideas faster, it cites itself as “discovery with a twist.” Yossarian uses AI when creating mood boards to return “diverse and unexpected concepts” that share loose associations with what you have searched for, allowing you to be more creative. It will source different ideas and inspiration around what you are searching for, including many you might not have thought of associating with your initial search term.

Brandmark

If you create logos and design templates within your work, Brandmark logo maker is a great AI tool to add to your library. They cite themselves as the most advanced AI logo design tool on the market at the moment. Whether logo creation is something you currently offer, or something you are looking to do, this AI tool can make it easier.

Autodraw

Autodraw is another useful tool you can use for design jobs, where you draw a rough sketch and it will turn it into a neat graphic. This is a handy one to use in association with the concept of sketch to code above. It pairs the magic of machine learning with drawings to help you create professional looking graphics and visuals, quickly.

[teqstories]

Top 6 Technology Trends for 2020

Technology has been evolving at a pace that the annual predictions about trends may seem to be outdated before they go live as a published blog post or article. The technology when evolves allows progress and change which accelerates the rate of change.

The careers that are based on technologies do not change at the same speed, rather they evolve and the IT professional know that their role is not going to be the same. In the current time, an IT professional will be found constantly learning one or the other thing not because of desire but may be out of necessity.

So it is necessary to keep your eyes on the future, to know the skills that you need to learn and the types of jobs you want to work in. Here are five technology trends for 2020 which will be acquired in the market:

1) ARTIFICIAL INTELLIGENCE

2) MACHINE LEARNING

3) INTERNET OF THINGS

4) DEVOPS

5) COGNITIVE EDGE COMPUTING

6) ANGULAR AND REACT AND VUE

So let us discuss the various technologies:

1) ARTIFICIAL INTELLIGENCE :

Artificial Intelligence or AI has been existing for a long time and also has received a lot of buzz in recent years. AI refers to computer systems that mimic human intelligence and performs tasks like recognition of images, speech and decision making. AI can do tasks faster and accurately than humans. AI is used in services like navigation app, scheduling trains, improving energy efficiency, streaming services, smart devices, and access business risks; predict maintenance and many other money-saving tasks.

AI is a part of automation. Automation is developing jobs and reducing a lot of human effort and costs in the technical field. To name a few job developments, testing, programming, support and maintenance jobs will be created.

2) MACHINE LEARNING:

Machine Learning is a subset of AI. The computers are programmed to learn to do something. They are given sets of data and they predict certain aspects of business by discovering patterns in the given sets of data. The types of learning can be classified as: supervised and unsupervised. While ML is a subset of AI, we also have subsets in the domain of ML which include neural networks, Natural Language Processing (NLP) and Deep Learning. Each subset offers an opportunity for specializing in a career field.

Machine Learning is creating a huge demand for skilled professionals as it is rapidly deployed in all kinds of industries. Machine Learning jobs rank among top trending jobs on LinkedIn. Machine learning applications are used for data analytics, data mining. And if seen from the consumer end, ML powers web search results, real-time ads to name a few.

3) INTERNET OF THINGS:

Many things that are built with Wifi connectivity which means they can be connected to each other is called as Internet of Things or IoT. IoT is the future and has already enabled devices, home appliances and much more to be connected to and exchange data over the internet. We can say we are only at the beginning stage of IoT. As consumers, we are already using and benefitting from IoT. For eg: When we leave home without a locking door we can lock it remotely or the Fitbit that tracks our fitness. The IoT can enable better safety, efficiency, and decision making for business as data is collected and analyzed. It can enable predictive maintenance, improved customer service and offer benefits we haven’t even imagined yet.

Despite this benefit in the development and adoption of IoT, experts say there are not enough IT professionals trained for IoT jobs. The skills that you need to develop are IoT security, Cloud computing knowledge to name a few. To sum up, it’s the Internet of Things and there are plenty of skills that are needed.

4) DEVOPS:

The DevOps started to merge in the IT industry somewhere between 2007 and 2008 when IT operations and software development section spoke about the level of dysfunction in the industry. Developers and IT professionals had separate objectives, key performance indicators by which they were judged. This resulted in siloed teams and things worsened in IT prospects. So the two sections combined together for conversation and the team got this theme which we are discussing now.

DevOps is a process in which a set of tools are implemented to automate the process between software development and IT team, to build, test and release software faster and more reliable. The concept of DevOps is set up on building a culture of collaboration between teams that historically functioned in relative silos. The benefits include faster software releases, the ability to solve critical issues quickly and better manageable unplanned work.

5) EDGE COMPUTING:

Cloud computing has become mainstream in today’s world. The players of cloud computing are AWS (Amazon Web Services), Microsoft Azure and Google Cloud dominating the market. The businesses are migrating to cloud station as the adoption of cloud computing is growing. But it is not an emerging technology.

We have realized the shortcomings of cloud computing in some situations as the quantity of data we are dealing with tends to increase. In order to solve the problems to bypass the latency caused by cloud computing and getting data to a data center for processing, edge computing is designed to help solve some of the problems. Edge computing can exist “on the edge”, somewhere close to the point where computing needs to happen. Thus edge computing is used to process time-sensitive data in remote locations with limited or no connectivity to a centralized location. In this situation, edge computing act like mini datacenters. Edge computing will be increasing as the use of Internet of Things (IoT) devices increases. Thus this will be creating various jobs in the market basically for software engineers.

6) ANGULAR AND REACT AND VUE:

It has been quite a few years now when web applications have captured the market completely. And hence started the battle of the best JavaScript framework. The Tech Giants have come up with a lot of Revolutionary JavaScript frameworks. However, deciding the best Javascript framework can be a pretty tedious task. ‘Angular vs React vs Vue’ is the current trending topic in 2020–2021. These frameworks come from a lineage of two powerful competitors — Google and Facebook. Among these three frameworks, React has already got a huge appreciation and therefore establishment in the industry. The newer flavor of Angular, however, is the most talked-about subject among the Webster.

Frameworks and libraries are shipped with different license agreements. Some vendors publish licenses that allow customization as per requirements and provide flexibility. Products with these categories of licenses are known as open-source products. The other category of licenses does not allow manipulations for designing of commercial applications without attributions.

React outweigh Angular and Vue. React observes higher downloads among the world websters. Vue closely follows React and is gaining rapid momentum, but Angular has remained the same for the past few years. React goes high on preference for its easier CSS markup.

Angular is preferred for large corporations, for its solid set of tools and quality community and the paid support. The Angular framework is considered more difficult for beginners as the learning curve is steep. React is relatively a mature product that is popular and appreciated among developers. The two key features of the product are immense flexibility and easy integration. Also, it is the most versatile option among the three. Vue has been existing for several years now but is relatively a newcomer. Some of the Asian companies have switched to Vue because of its quality. It is suited for fast-paced growth. Needless to say, all these three frameworks are perfectly suitable for mobile development in 2020.

So, even though technologies are emerging around us, these technologies are going to offer a promising career for the upcoming period. Right now these technologies are suffering a shortage of skilled employees which means it’s the right time for you to choose the one to get trained and develop your career.

[classicinformatics-blog]

Top 8 Web Development Trends To Watch Out In 2020

Web development is a dynamic and progressive field that keeps on changing as new technologies emerge. In the year 2020, web development will witness a plethora of possibilities that will set new trends.

In 2020, web developers will adopt new technologies, experiment with new techniques and reinvent previous techniques. At the same time, some web development trends of previous years won’t go away and will continue in the year 2020 and beyond.

Smart businesses look forward to new technologies and try to follow the emerging trends that can provide them a competitive edge. To build up-to-date products, businesses should hire web developers that keep themselves abreast of latest web development trends and technologies.

Here are the web development trends to watch out in 2020 –

Progressive Web Apps (PWAs)

A progressive web app is a web app that makes use of the latest web capabilities to provide an app-like experience. Progressive web apps are being considered as the next big thing for the users of the mobile web.

A progressive web app combines the best of both web and mobile apps. You can consider it as a website that acts and feels like a mobile app. Experts define progressive web apps as responsive, connectivity-independent, safe, linkable, re-engageable and app-like web experiences.

Pinterest saw a 60% increase in core engagements and 50% increase in ad click-throughs when it replaced its mobile website with a progressive web app.

Chatbots

A chatbot is a piece of software that processes and simulates human conversation. It allows people to interact with devices, apps or websites. A chatbot can be just a basic program that replies to a simple query or it may be a complex piece of software that can provide a high level of personalization to users.

To deliver responses to requests, chatbots make use of natural language processing (NLP), artificial intelligence and machine learning (ML). For businesses, chatbots enhance operational efficiency and save money. As many customer queries can be easily answered by chatbots, businesses require less number of customer service professionals.

According to Gartner, by the year 2021, artificial intelligence will be used to completely handle 15% of customer service interactions occurring worldwide. By the year 2022, about 70% of white-collar professionals will engage every day with conversational platforms.

WebAssembly

WebAssembly, also known as Wasm, has been designed by the World Wide Web Consortium (W3C) in order to enable high performance applications on the web. It is a portable binary instruction format for high-level languages’ compilation.

It is part of the open web platform, and is safe, efficient, fast and debuggable. As WebAssembly is a virtual instruction set architecture, it can be used in diverse cases and in many different environments. In December 2019, WebAssembly became a W3C recommendation. It is the fourth language to run natively in web browsers along with HTML, CSS, and JavaScript.

Single Page Applications (SPAs)

A single-page application (SPA) is a web app that loads as a single page and does not require loading of whole new pages. The content is loaded into the page dynamically. A user gets a smooth experience, free from any interruption, just like a desktop application. Common examples of SPAs are Gmail, Facebook, etc.

There is no extra wait time as the user visits just one web page and all the other content is loaded into this same page. Single-page applications (SPAs) offer many benefits such as fast loading, simplified development, easy debugging, reusability of same backend code for mobile app development, effective caching of any local data, and offline functioning.  

Motion UI

By using motion UI, a web development company is able to provide a superb user experience. Motion UI increases customer engagement with websites and apps. It can include a number of elements such as shapes, photos, text, 3D objects, illustrations, lines, videos, etc.

Motion UI finds use in a variety of settings such as welcoming users, system status and notifications, refreshing content, navigations and transitions, feedbacks, results of actions, acknowledgments, etc. It provides awesome experience to users and leaves a positive effect on the users’ minds. Motion UI is quite in trend and will remain so in 2020, as web and mobile app development companies are increasingly using it.

Accelerated Mobile Pages (AMP)

Accelerated mobile pages (AMP) are technically HTML copies of existing webpages. They are lightweight, stripped-down and fast-loading pages. AMP technology makes use of stripped-down HTML, stripped-down JS, and a content delivery network (CDN) that is optimized to cache pages and to adapt them to accelerated mobile pages (AMP) code.

AMP technology significantly enhances the performance of the mobile web. With AMP, people using mobile devices to access content get significantly fast page load times. By using AMP, mobile-friendliness of websites increases.

In May 2017, the number of domains using AMP was 900,000. In early 2018, this number rose to 31 million domains. This means an increase of more than 34 times. AMP is trending as more and more domains are adopting it.

Voice Search

Voice search is a technology that allows users to speak into a device to generate results. This is in sharp contrast to typing keywords into a search box and hitting the Enter key. This technology makes use of speech recognition program to understand users’ words accurately so that appropriate results can be delivered.

Some of the examples of voice search technology that are in use include Google Assistant, Siri from Apple, Cortana from Microsoft, Alexa from Amazon, etc. Voice search significantly improves user experience, and that is why more and more websites are being optimized for it.

According to Comscore, by the year 2020, 50% of all online searches will be performed with voice search. According to Gartner, by the year 2021, early adopter brands that redesign their websites to support visual and voice search will increase digital commerce revenue by 30%.

JavaScript and Python

According to Stack Overflow’s annual developer survey 2019, for the last seven years, JavaScript has been continuously ranked as the most commonly used programming language. Python has emerged as the fastest-growing major programming language.

Both JavaScript and Python are used by web and mobile app developers. Python offers benefits such as numerous third-party modules, vast library, easy to learn, user-friendly data structures, community-driven development and support, etc.

The main reason for JavaScript’s popularity is that it offers many advantages such as it is very fast, compilation on the client side is not required, simple to learn, easy to implement, compatible with other languages, can be used in a vast variety of applications, can be used in any webpage, can be included in scripts written in other languages, reduces load on website server, etc. Businesses can hire JavaScript developers to build top-notch web and mobile apps.    

The above technologies that will trend in the year 2020 will have transformative impact on the web development industry. By leveraging the most suitable trending technology, a business can create powerful websites and apps that can provide enhanced user experience and help boost business productivity.

Source: https://www.classicinformatics.com/blog/top-web-development-trends-2020

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How Developers Can Deliver Chatbots that Propel a Broader AI Strategy

A basic chatbot isn’t that hard to build. In JavaScript, write a public REST endpoint to connect a Facebook page to some chat logic (botly is a popular option) and deploy the whole thing to run on a cloud platform.

Zoom out to the bigger picture, though, and you see that Facebook is just one channel. If you use Skype, Slack, Kik, and digital voice assistants, you’ll have to build six or eight of these endpoints straight away. And chatbots are being asked to handle ever more complex responses, so you better build on a platform of machine learning and natural language processing to keep up.

That’s why the question enterprise developers should be asking is not “Which chatbot service do I start with?” but “Which platform will let me crank out a chatbot today and also support multiple channels and integrate with back-end systems as these chatbots take off?”

Check out the webcast: Conversational bots driven by AI

Answering these questions can put a chatbot project at the hub of a wider enterprise artificial intelligence effort—providing a tangible use case without the confusion that a bottom-up AI effort can entail.

“We’ve taken a completely different approach to applying AI,” says Suhas Uliyar, vice president of mobile, bot, and AI strategy and product management for Oracle. “We are using the bot use case to bring in AI algorithms for deep learning, cognitive services, dialog and context, and knowledge services, and fine tune them for chatbots, which enterprises are prioritizing as their AI use case today.”

So where do you start with an intelligent chatbot project? Uliyar urges developers to focus on these four concepts.

1. Channels represent a surprising amount of complexity.

“Take SMS or Facebook Messenger or Skype. The way instant messaging works is the same: you type something, you hit return, and it responds back. But the look and feel is very different. A menu structure in Messenger is not even supported in SMS. As a developer, I need to figure out the best way to provide a delightful experience on the channel itself,” Uliyar says, noting that Facebook, Line, Telegram, and others are each also expanding the use of graphics.

There is no standard among these social networks for prioritization, routing, or error handling—and different channels are popular in different regions.

“You could say, well, I’ll just stick to Facebook Messenger,” Uliyar says. “But if you go to Japan, for instance, Line is the number one messaging platform. If you look to China, it’s WeChat. In India, it’s WhatsApp. If you go to Malaysia, it’s Telegram.” There are also voice-based personal assistants and voice services on mobile phones. Uliyar notes that many organizations are still skeptical about these consumer-oriented channels, but want to start by offering bot services as an extension to their mobile app and on their corporate website. “So it’s not like you could say, ‘I’ll just pick one, and the world will follow,’” Uliyar says.

For these reasons, a chatbot platform that abstracts channel complexity, so a developer can write a conversation script one time for use on many channels, is a productivity booster while delivering the real business value of personalized engagement with the end user.

With Oracle Mobile Cloud Enterprise (OMCe), developers get a multichannel platform to engage with customers and employees across all of today’s most popular messaging, mobile and web platforms. It also brings together channels, dialog flow, an AI engine, and integration with bot builder capabilities.

2. Tuning your machine learning to understand user intent is non-trivial, so your technology platform should take care of that.

There are several open source machine learning libraries for natural language understanding that developers that can embed, but just embedding these libraries isn’t enough. The public core natural language processing (NLP) and machine learning algorithms have become commodities that are basic pieces of the total solution.

Using NLP and ML is a system design problem where the developer needs to consider the target use cases, design and operating environment, and available data, Uliyar says. This determines the workflow design, data integration, pre-processing, meaning extraction approach, desired outputs, tools, and operational requirements. NLP and ML algorithms are driven by these considerations. The specific combination and models are then designed accordingly and are tuned for this system design, including unique extensions and inventions.

Enter two concepts universal to machine learning: supervised and unsupervised learning.

You use supervised learning, or classification, when your organization doesn’t have a lot of well-organized data that can teach your algorithm. Most enterprises are in this situation as they get started. In this model, an administrator trains the bot through conversational logs created through increasing interactions with bot users.

You use unsupervised learning, or clustering, when you have a lot of data. The model can go through a transcript analyzer to reduce many of the steps required in supervised learning and auto-generate models that the bot can use as a starting point. An algorithm trains on vast amounts of unlabeled data to do things like searching documents or sounds, segmenting customers by similar traits, and optimizing data center topology by usage metrics.

“The more data you have, the more accurate your predictions become,” Uliyar says, but a vast amount isn’t necessary. Your platform should handle both supervised and unsupervised learning.

3. A good dialog engine leads to context-appropriate conversations.

“You and I have different ways of asking how much money we have: ‘Hey, what’s my balance?’ or ‘What’s my checking balance?” Uliyar says. A neural network-based algorithm needs to understand that. “But on top of that, the developer needs to build a conversation that lets an end user converse with the bot,” Uliyar says.

Dialog creation is as critical to bot adoption as the UI experience is for a mobile app. So having a strong dialog builder and some best practices on designing conversations is crucial.

Dialog creation allows the bot to respond in multiple ways to discover user intent, as well as extract all the necessary information to give an appropriate response, such as figuring out which of three bank accounts a customer is referring to. Expressive scripts, based on topics around typical enterprise use cases, help the dialog engine generate—and learn from—human-like conversations. Sentence analysis and question tagging, plus databases for words and concepts, are key features you’ll need.

4. Enterprise integration wraps up the total package.

Chatbots are most powerful when they can directly pull data and insights from systems of record, be they financial, enterprise resource planning, customer relationship management, or any kind of data source. That’s why at least 70% of the work to build an actionable bot will be integration to provide context to the dialog with the end user, Uliyar says. And it’s why Oracle Mobile Cloud Enterprise provides support out of the box for APIs to connect to back-end systems that can be leveraged across mobile, web and chatbots. With the introduction Oracle’s Intelligent Bots, Oracle will be able to embed chatbot capabilities into its cloud applications, and developers will be able to customize their bots to meet the needs of an industry such as retail or finance or a department like finance or HR.

“The messaging channels are becoming the new browser,” Uliyar says.

But chatbots can’t solve every problem. Chatbots are wonderful for quick request and response interactions, Uliyar says, but forms are a better experience for collecting or reviewing a lot of structured data. For example, a banking bot is a great way to check your balance or ask for current interest rates, but not great at filling out a form to apply for a loan. So Uliyar advocates having an architecture and strategy where the bot is intelligent enough to surface the right process via a mobile app at the right time. To do that, he thinks mobile apps will go through a major change from monolithic apps to contextual, purpose-built apps, very similar to the strategy of turning monolithic services into microservices and functions.

“You’ll be hearing new terminology at Oracle OpenWorld—‘instant apps,’” he says. “Our definition of a mobile app is to decompose it into functional components instead of one monolithic mobile app that does everything.”

  https://blogs.oracle.com/how-developers-can-deliver-chatbots-that-propel-a-broader-ai-strategy

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