#ML technology

[primathontechnology]

The Role of Machine Learning in Modern Software Development

Explore how machine learning is used in modern software development. Learn about its impact on automation, problem-solving, and enhancing user experiences in today’s tech-driven world. AI and ML development tools, including TensorFlow, PyTorch, and Scikit-learn, are the features of modern software trends as they capture the way applications are designed and deployed.

[gleecus-techlabs-blogs]

Machine Learning (ML), a type of artificial intelligence (AI), has been shown to be beneficial in many industries. ML systems can automatically learn and improve from experience without being explicitly programmed. They do this by accessing data and learning from it. This makes ML a powerful tool for the oil and gas industry, where there is a vast amount of data available.

[anna-scribbles]

i think it would be funny if one of the ways that adrien responded to Everything was by becoming the most offline unreachable hermit of all time. no phone no computer nothing. don’t talk to him about ai or instagram brand deals or twitter drama he can’t even receive a text message. if you want to contact him he checks his email once a week at the local library. he also has a flip phone with customized ringtones and no internet connection, and a number he gives out to an extremely select list of people. don’t try to reference a pop culture phenomenon to him he won’t understand it. his flip phone can’t open tiktoks. he’s protecting his peace.

[queen-mabs-revenge]

I'm just saying maybe you shouldn't talk about the Luddites if you actually refuse to engage with their historical struggle and the reasons for it and instead just perpetuate the bourgeois propaganda about them and somehow act that's the materialist take. get fucking serious please.

[noahboswel]

Great Article By Ashkan Rajaee

[giovannivi95552]

Great Article By Ashkan Rajaee

[burikumu]

Sharing my "ideal" study schedule weeks before the MTLE March 2024 (Board Exam)

Of course this didn't happen/ there were some adjustments made 😅

Also I'm not sure what I was doing. I might go on a little bit of more detail about the schedule on the NEXT POST.

What I did basically:

SCHEDULING

I've allotted Sunday as my rest day and scheduled my breaks.

Each subject, supposedly covers 4 hours (but I miscalculated the other times of the day and only became about 3 hrs, hence the adjustments)

INTERLEAVING

Since I had a lot of subjects to cover I've tried to incorporate this method instead of blocking.

Videos that helped me in Scheduling and Interleaving:

How to study MANY SUBJECTS without crying from stress & regret 😭 by fayefilms

A Science based System for Learning ANYTHING quickly by Python Programmer

How to study multiple subjects by Koi Academy

Videos that help me to understand revision and other study methods:

Lecture #9: How to Read so that you *Retain* Information by Jeffrey Kaplan

Spend 1 Hour Studying to Save 20 Hrs Later by Justin Sung

Study With Me (Live) - Guided Technique Walkthrough by Justin Sung

How to Revise EFFICIENTLY | STUDY CLINIC by Justin Sung

The Ultimate Speed Learning Tutorial (Learning in Layers) by Koi Academy

How Do You Revise for an Exam? (Live Coaching | JUST-IN-CASE) by Justin Sung

[fraoula1]

Python for Data Science: From Beginner to Expert – A Complete Guide!

Python has become the go-to language for data science, thanks to its flexibility, powerful libraries, and strong community support. In this video, we’ll explore why Python is the best choice for data scientists and how you can master it—from setting up your environment to advanced machine learning techniques.

🔹 What You'll Learn:

✅ Why Python is essential for data science

✅ Setting up Python and key libraries (NumPy, Pandas, Matplotlib) ✅ Data wrangling, visualization, and transformation

✅ Building machine learning models with Scikit-learn

✅ Best practices to enhance your data science workflow 🚀 Whether you're a beginner or looking to refine your skills, this guide will help you level up in data science with Python. 📌 Don’t forget to like, subscribe, and hit the notification bell for more data science and Python content!

[hawkeyedaniel]

Great Article By Ashkan Rajaee

[khushidubeyblog]

PGDM Specialization in AI & ML: Preparing for the Future of Business and Technology

[aionlinemoney]

The Role of Machine Learning Engineer: Combining Technology and Artificial Intelligence

Artificial intelligence has transformed our daily lives in a greater way than we can’t imagine over the past year, Impacting how we work, communicate, and solve problems. Today, Artificial intelligence furiously drives the world in all sectors from daily life to the healthcare industry. In this blog we will learn how machine learning engineer build systems that learn from data and get better over time, playing a huge part in the development of artificial intelligence (AI). Artificial intelligence is an important field, making it more innovative in every industry. In the blog, we will look career in Machine learning in the field of engineering.

What is Machine Learning Engineering?

Machine Learning engineer is a specialist who designs and builds AI models to make complex challenges easy. The role in this field merges data science and software engineering making both fields important in this field. The main role of a Machine learning engineer is to build and design software that can automate AI models. The demand for this field has grown in recent years. As Artificial intelligence is a driving force in our daily needs, it become important to run the AI in a clear and automated way.

A machine learning engineer creates systems that help computers to learn and make decisions, similar to human tasks like recognizing voices, identifying images, or predicting results. Not similar to regular programming, which follows strict rules, machine learning focuses on teaching computers to find patterns in data and improve their predictions over time.

Responsibility of a Machine Learning Engineer:

Collecting and Preparing Data

Machine learning needs a lot of data to work well. These engineers spend a lot of time finding and organizing data. That means looking for useful data sources and fixing any missing information. Good data preparation is essential because it sets the foundation for building successful models.

Building and Training Models

The main task of Machine learning engineer is creating models that learn from data. Using tools like TensorFlow, PyTorch, and many more, they build proper algorithms for specific tasks. Training a model is challenging and requires careful adjustments and monitoring to ensure it’s accurate and useful.

Checking Model Performance

When a model is trained, then it is important to check how well it works. Machine learning engineers use scores like accuracy to see model performance. They usually test the model with separate data to see how it performs in real-world situations and make improvements as needed.

Arranging and Maintaining the Model

After testing, ML engineers put the model into action so it can work with real-time data. They monitor the model to make sure it stays accurate over time, as data can change and affect results. Regular updates help keep the model effective.

Working with Other Teams

ML engineers often work closely with data scientists, software engineers, and experts in the field. This teamwork ensures that the machine learning solution fits the business goals and integrates smoothly with other systems.

Important skill that should have to become Machine Learning Engineer:

Programming Languages

Python and R are popular options in machine learning, also other languages like Java or C++ can also help, especially for projects needing high performance.

Data Handling and Processing

Working with large datasets is necessary in Machine Learning. ML engineers should know how to use SQL and other database tools and be skilled in preparing and cleaning data before using it in models.

Machine Learning Structure

ML engineers need to know structure like TensorFlow, Keras, PyTorch, and sci-kit-learn. Each of these tools has unique strengths for building and training models, so choosing the right one depends on the project.

Mathematics and Statistics

A strong background in math, including calculus, linear algebra, probability, and statistics, helps ML engineers understand how algorithms work and make accurate predictions.

Why to become a Machine Learning engineer?

A career as a machine learning engineer is both challenging and creative, allowing you to work with the latest technology. This field is always changing, with new tools and ideas coming up every year. If you like to enjoy solving complex problems and want to make a real impact, ML engineering offers an exciting path.

Conclusion 

Machine learning engineer plays an important role in AI and data science, turning data into useful insights and creating systems that learn on their own. This career is great for people who love technology, enjoy learning, and want to make a difference in their lives. With many opportunities and uses, Artificial intelligence is a growing field that promises exciting innovations that will shape our future. Artificial Intelligence is changing the world and we should also keep updated our knowledge in this field, Read AI related latest blogs here.

[ogxfuturetech]

The Comprehensive Guide to Web Development, Data Management, and More 

Introduction 

Everything today is technology driven in this digital world. There's a lot happening behind the scenes when you use your favorite apps, go to websites, and do other things with all of those zeroes and ones — or binary data. In this blog, I will be explaining what all these terminologies really means and other basics of web development, data management etc. We will be discussing them in the simplest way so that this becomes easy to understand for beginners or people who are even remotely interested about technology.  JOIN US

What is Web Development? 

Web development refers to the work and process of developing a website or web application that can run in a web browser. From laying out individual web page designs before we ever start coding, to how the layout will be implemented through HTML/CSS. There are two major fields of web development — front-end and back-end. 

Front-End Development 

Front-end development, also known as client-side development, is the part of web development that deals with what users see and interact with on their screens. It involves using languages like HTML, CSS, and JavaScript to create the visual elements of a website, such as buttons, forms, and images. JOIN US

HTML (HyperText Markup Language): 

HTML is the foundation of all website, it helps one to organize their content on web platform. It provides the default style to basic elements such as headings, paragraphs and links. 

CSS (Cascading Style Sheets):  

styles and formats HTML elements. It makes an attractive and user-friendly look of webpage as it controls the colors, fonts, layout. 

JavaScript :  

A language for adding interactivity to a website Users interact with items, like clicking a button to send in a form or viewing images within the slideshow. JOIN US

Back-End Development 

The difference while front-end development is all about what the user sees, back end involves everything that happens behind. The back-end consists of a server, database and application logic that runs on the web. 

Server: 

A server is a computer that holds website files and provides them to the user browser when they request it. Server-Side: These are populated by back-end developers who build and maintain servers using languages like Python, PHP or Ruby. 

Database:  

The place where a website keeps its data, from user details to content and settings The database is maintained with services like MySQL, PostgreSQL, or MongoDB. JOIN US

Application Logic —  

the code that links front-end and back-end It takes user input, gets data from the database and returns right informations to front-end area. 

Why Proper Data Management is Absolutely Critical 

Data management — Besides web development this is the most important a part of our Digital World. What Is Data Management? It includes practices, policies and procedures that are used to collect store secure data in controlled way. 

Data Storage –  

data after being collected needs to be stored securely such data can be stored in relational databases or cloud storage solutions. The most important aspect here is that the data should never be accessed by an unauthorized source or breached. JOIN US

Data processing:  

Right from storing the data, with Big Data you further move on to process it in order to make sense out of hordes of raw information. This includes cleansing the data (removing errors or redundancies), finding patterns among it, and producing ideas that could be useful for decision-making. 

Data Security:  

Another important part of data management is the security of it. It refers to defending data against unauthorized access, breaches or other potential vulnerabilities. You can do this with some basic security methods, mostly encryption and access controls as well as regular auditing of your systems. 

Other Critical Tech Landmarks 

There are a lot of disciplines in the tech world that go beyond web development and data management. Here are a few of them: 

Cloud Computing 

Leading by example, AWS had established cloud computing as the on-demand delivery of IT resources and applications via web services/Internet over a decade considering all layers to make it easy from servers up to top most layer. This will enable organizations to consume technology resources in the form of pay-as-you-go model without having to purchase, own and feed that infrastructure. JOIN US

Cloud Computing Advantages:  

Main advantages are cost savings, scalability, flexibility and disaster recovery. Resources can be scaled based on usage, which means companies only pay for what they are using and have the data backed up in case of an emergency. 

Examples of Cloud Services: 

Few popular cloud services are Amazon Web Services (AWS), Microsoft Azure, and Google Cloud. These provide a plethora of services that helps to Develop and Manage App, Store Data etc. 

Cybersecurity 

As the world continues to rely more heavily on digital technologies, cybersecurity has never been a bigger issue. Protecting computer systems, networks and data from cyber attacks is called Cyber security. 

Phishing attacks, Malware, Ransomware and Data breaches: 

This is common cybersecurity threats. These threats can bear substantial ramifications, from financial damages to reputation harm for any corporation. 

Cybersecurity Best Practices:  

In order to safeguard against cybersecurity threats, it is necessary to follow best-practices including using strong passwords and two-factor authorization, updating software as required, training employees on security risks. 

Artificial Intelligence and Machine Learning 

Artificial Intelligence (AI) and Machine Learning (ML) represent the fastest-growing fields of creating systems that learn from data, identifying patterns in them. These are applied to several use-cases like self driving cars, personalization in Netflix. 

AI vs ML —  

AI is the broader concept of machines being able to carry out tasks in a way we would consider “smart”. Machine learning is a type of Artificial Intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. JOIN US

Applications of Artificial Intelligence and Machine Learning: some common applications include Image recognition, Speech to text, Natural language processing, Predictive analytics Robotics. 

Web Development meets Data Management etc. 

We need so many things like web development, data management and cloud computing plus cybersecurity etc.. but some of them are most important aspects i.e. AI/ML yet more fascinating is where these fields converge or play off each other. 

Web Development and Data Management 

Web Development and Data Management goes hand in hand. The large number of websites and web-based applications in the world generate enormous amounts of data — from user interactions, to transaction records. Being able to manage this data is key in providing a fantastic user experience and enabling you to make decisions based on the right kind of information. 

E.g. E-commerce Website, products data need to be saved on server also customers data should save in a database loosely coupled with orders and payments. This data is necessary for customization of the shopping experience as well as inventory management and fraud prevention. 

Cloud Computing and Web Development 

The development of the web has been revolutionized by cloud computing which gives developers a way to allocate, deploy and scale applications more or less without service friction. Developers now can host applications and data in cloud services instead of investing for physical servers. 

E.g. A start-up company can use cloud services to roll out the web application globally in order for all users worldwide could browse it without waiting due unavailability of geolocation prohibited access. 

The Future of Cybersecurity and Data Management 

Which makes Cybersecurity a very important part of the Data management. The more data collected and stored by an organization, the greater a target it becomes for cyber threats. It is important to secure this data using robust cybersecurity measures, so that sensitive information remains intact and customer trust does not weaken. JOIN US

Ex: A healthcare provider would have to protect patient data in order to be compliant with regulations such as HIPAA (Health Insurance Portability and Accountability Act) that is also responsible for ensuring a degree of confidentiality between a provider and their patients. 

Conclusion 

Well, in a nutshell web-developer or Data manager etc are some of the integral parts for digital world.

As a Business Owner, Tech Enthusiast or even if you are just planning to make your Career in tech — it is important that you understand these. With the progress of technology never slowing down, these intersections are perhaps only going to come together more strongly and develop into cornerstones that define how we live in a digital world tomorrow. 

With the fundamental knowledge of web development, data management, automation and ML you will manage to catch up with digital movements. Whether you have a site to build, ideas data to manage or simply interested in what’s hot these days, skills and knowledge around the above will stand good for changing tech world. JOIN US

[simple-logic]

Which is a command to create a new directory? 🗂️

a) mkdir 🖥️

b) mkdir -p 🛠️

c) create dir 🚫

d) newdir 🚪

📂 Time for a tech challenge!

Comment your answer below

[grey-space-computing]

Deliver personalized user experiences with machine learning in your app. Understand your users better and give them exactly what they need. 🔗Learn more: https://greyspacecomputing.com/custom-mobile-application-development-services/  📧 Visit: https://greyspacecomputing.com/portfolio

[burikumu]

04.21.25 (Mon)

From extracting 5 patients an hour to 8!!! Small steps, small steps. I know it's not much, I still have a lot to improve in phlebotomy 🙂.