Core Machine Learning Concepts Explained | Practical & Visual Tutorial for Beginners (2025) | скачать в хорошем качестве

Core Machine Learning Concepts Explained | Practical & Visual Tutorial for Beginners (2025) |

🔹Unlock the Core Machine Learning Concepts with this visual + practical tutorial (2025 edition)! Whether you’re a beginner stepping into the world of data science or someone looking to strengthen your foundation in AI & ML, this video will guide you through the essential principles that every aspiring data scientist must know. ------------------------------------------------------------------------------------------------------------------------- 🔑 What you’ll learn in this video: • What is Machine Learning? • Types of Machine Learning (Supervised, Unsupervised, Reinforcement Learning) • Core concepts: features, labels, training & testing datasets • Overfitting vs Underfitting explained visually • Practical examples with real-world ML applications • A simple hands-on ML demo/tutorial 📊 This video blends theory + visuals + coding snippets so you can learn faster and retain better. ------------------------------------------------------------------------------------------------------------------------- 🌟 Why watch this video? Machine Learning is the heart of Artificial Intelligence, and understanding its core concepts is the first step towards becoming a Data Scientist, ML Engineer, or AI Specialist in 2025 and beyond. ------------------------------------------------------------------------------------------------------------------------- 🔗 Useful Resources & Links: 📘 Official Documentation & Tutorials 🔹Scikit-learn Documentation → https://scikit-learn.org/stable/ 🔹TensorFlow Tutorials → https://www.tensorflow.org/tutorials 🔹PyTorch Tutorials → https://pytorch.org/tutorials/ 🔹Keras API Reference → https://keras.io/ 📊 Practice Datasets & Projects 🔹Kaggle Datasets → https://www.kaggle.com/datasets 🔹Google Dataset Search → https://datasetsearch.research.google... 🔹UCI Machine Learning Repository → https://archive.ics.uci.edu/ml/index.php 📚 Books & Learning Resources 🔹Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow → https://amzn.to/4pc77Fi 🔹Deep Learning with Python by François Chollet → https://amzn.to/4mRZN0f 🔹Pattern Recognition and Machine Learning by Christopher Bishop : https://amzn.to/4m0dKrp 🔹Machine Learning with PyTorch and Scikit-Learn by Sebastian Raschka : https://amzn.to/4mQXYjX ------------------------------------------------------------------------------------------------------------------------- 🎓 Free Courses Machine Learning (Andrew Ng – Coursera) → https://www.coursera.org/learn/machin... Deep Learning Specialization (Andrew Ng – Coursera) → https://www.coursera.org/specializati... Intro to Machine Learning (Kaggle Learn) → https://www.kaggle.com/learn/intro-to... Fast.ai Practical Deep Learning → https://course.fast.ai/ ------------------------------------------------------------------------------------------------------------------------- OUTLINE: 00:00:00 → What is Machine Learning? 00:00:58 → Types of Machine Learning 00:02:29 → Features and Labels Fundamentals 00:04:19 → Overfitting and Underfitting 00:06:37 → Bias and Variance Trade-off 00:08:20 → Popular Algorithms and Code 00:10:46 → Real-World Applications 00:12:42 → Future of ML and Learning Path 00:14:44 → Final Encouragement and Call to Action --------------------------------------------------------------------------------------------------------------------------- ✅ Stay Connected: 🔔 Subscribe for more Data Science & AI content:    / @the_data_key   👍 Like, Share & Comment your thoughts – it helps us grow! 📩 Follow for updates:   / the-data-key   #MachineLearning #DataScience #AI #TheDataKey #MLTutorial #ArtificialIntelligence #CodingForBeginners #freecourse #studymaterial #DataAnalytics #MachineLearning #BigData #DeepLearning #ArtificialIntelligence #AI #DataVisualization #TheDataKey #DataScienceWithTheDataKey #LearnWithTheDataKey #foryou