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Understand SVM – a powerful ML algorithm for classification and regression. Learn with TCCI Ahmedabad.

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Machine Learning Course in Kolkata | Skillfloor Learn the basics of Machine Learning 🤖📊 with hands-on projects in Kolkata! 🏙️ Boost your skills for the future 🚀 with Skillfloor. Learn More: https://skillfloor.com/artificial-intelligence-training-in-kolkata

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Applied Machine Learning Online Training | Machine Learning (ML)

Visualpath is one of the best Applied Machine Learning Online Training in Ameerpet. We are providing Live Instructor-Led Online Classes delivered by experts from Our Industry. We will provide live project training after course completion. Enroll Now!! Contact us +91-9989971070.

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Our comprehensive Machine Learning Course in Noida is designed by industry experts to provide hands-on experience and deep insights into machine learning concepts and algorithms. Whether you are a beginner or an experienced professional looking to upskill, our course caters to all levels of expertise.

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Playlist Premiere | Session 0 : AI/ML Essential Series 1 | High Level overview of AI/ML concept

Welcome to the premiere of our AI/ML Essential Series! In Session 0, we kickstart our journey by providing a comprehensive high-level overview of AI/ML concepts. Whether you're new to the world of Artificial Intelligence (AI) and Machine Learning (ML) or seeking a refresher, this session is designed to lay the groundwork for understanding key principles and terminology.

Subscribe to "Learn And Grow Community" YouTube : https://www.youtube.com/@LearnAndGrowCommunity LinkedIn Group : https://linkedin.com/company/LearnAndGrowCommunity Follow #learnandgrowcommunity

[hoursofreading]

ExplainPaper

[teguhteja]

Stop feeling lost in Machine Learning! Get our essential tutorial list covering foundations, algorithms, math & more. Start mastering ML today! #MachineLearning #DataScience #Python #Tutorial #LearnML

[tccicomputercoaching]

SVM Algorithm Explained – TCCI Ahmedabad

Support Vector Machines (SVMs) are supervised machine learning algorithms employed in classification and regression tasks.

Hyperplane: A hyperplane separates data points of different classes in feature space; it can also be called a decision boundary.

Mathematical Representation: w•x + b = 0

Example:

For instance, if we will classify animals as cat (+1) and dog (-1) by weight and height, then the hyperplane could be

3×Weight + 2×Height - 50 = 0

Support Vectors: These data points are the nearest ones to hyperplane. These points influence the orientation and position of hyperplane.

Margin: The margin is the distance between hyperplane and the nearest data point of either class; SVM tries to maximize margin to increase confidence of classifications.

Hard Margin: Assuming that the data is perfectly separable by hyperplane. Therefore, all points must lie outside of the margin.

Soft Margin: It allows a few misclassifications or margin violations for non-linearly separable data.

Kernel Function: Kernel function transforms the data into higher dimensional space to make it linearly separable.

Types of Kernels:

Linear Kernel: Suitable for linearly separable data.

Polynomial Kernel: For curved boundaries.

Radial Basis Function (RBF): Captures complex relationships.

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[learnandgrowcommunity]

Session 18 : Quick Recap | AI/ML Essential | Concept overview for AI/ML Beginners

Welcome to Session 18 of our AI/ML Essentials series! In this session, we provide a quick recap of key concepts covered so far, making it easier for beginners to catch up and reinforce their understanding of artificial intelligence and machine learning. Whether you're just starting your journey into AI/ML or looking to refresh your knowledge, this concise overview will help you grasp fundamental concepts and build a solid foundation. Dive in and deepen your understanding of the fascinating world of AI and ML! Don't forget to like, subscribe, and hit the notification bell to stay updated on future sessions.

Subscribe to "Learn And Grow Community" Follow #learnandgrowcommunity

[aionlinecourse]

Introduction to Machine Learning

We live in a data-driven world, creating 2.5 quintillion bytes daily! 💾 Machine learning helps us make sense of this data, from Google searches to Amazon recommendations. 🤖✨

Want to know how it works? Here’s a quick look: 1️⃣ Supervised Learning: Learns from labeled data. 2️⃣ Unsupervised Learning: Finds patterns in unlabeled data. 3️⃣ Reinforcement Learning: Learns from rewards and penalties.

Machine learning is everywhere - image recognition, voice assistants like Siri and Alexa, personalized ads, and even healthcare! 🏥💡 Learn more: https://www.aionlinecourse.com/tutorial/machine-learning/introduction-in-machine-learning

Start your journey with our easy-to-follow tutorial. Happy Learning! 🚀

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[paravisionlab]

This colorful infographic demystifies the concept of transfer learning in machine learning. It illustrates how a pre-trained source model serves as a foundation for a target model, which is then fine-tuned with new data for specific tasks. The flowcharts depict the process from input to output using the source model and the transfer of knowledge to the target model. Neural network layers, including convolutional (CNN) and fully connected (FC) layers, adapt to classify thousands of classes in the source model and binary classes in the target model.

🎨 Why It’s Interesting:

Simplifies a complex topic for learners.

Engages viewers with vibrant visuals.

Makes transfer learning accessible.

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[teguhteja]

Machine Learning Sklearn and TensorFlow : Course Path

#MachineLearning #DataScience #PythonProgramming #Sklearn #TensorFlow #AI #DeepLearning #DataPreprocessing #FeatureEngineering #MLJourney #LearnML #TechSkills #DataCleaning #MLModels

Introduction Curious about machine learning using Sklearn and Tensorflow but unsure where to start? Look no further! Our carefully curated learning path, designed for Python programmers and data scientists, takes you from the fundamentals of Sklearn to the advanced realms of deep learning with TensorFlow. Whether you’re brushing up on data cleaning or diving into neural networks, this journey…

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Revolutionising every data-driven industry, #MachineLearning and #ArtificialIntelligence are redefining the future! You too can become a part of this growth with skills-oriented training at #AptechLearning. Learn everything from scratch and work up your way on being a #MachineLearningEngineer upon successful completion of the course. Enhance your skillset with specialisation in Python, MongoDB & R Studio. Become a #JobReady professional. Enrol now

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[adjustedme]

What is Data Science? - The Many Paths to Data Science by IBM #2

Read the full article

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