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[Intro - The "Why"] Stop guessing how AI works. In this video, we break down the Machine Learning Fundamentals that power the modern world. From data training to neural networks, we explain the "how" and the "why" in just 14 minutes. [The "What"] Whether you're a student, a developer, or just curious about the future, this Thinkron guide simplifies the complex logic behind the algorithms. 🚀 Topics Covered: The Core Definition: What is ML vs. Traditional Programming? The Three Pillars: Supervised, Unsupervised, and Reinforcement Learning. The Process: Data collection, Feature Engineering, and Model Training. The Reality: Why models fail and how we fix them. ⏱️ CHAPTERS: 0:00 — Why ML Matters Now 2:15 — The Definition of "Learning" in Machines 4:30 — Supervised vs Unsupervised (The Simple Way) 7:45 — Neural Networks & Deep Learning Basics 10:20 — Real-World Use Cases (2026 Edition) 13:00 — How to Start Your ML Journey 🧠 Connect with Thinkron: If you love deep dives into Physics, Tech, and the future of logic, subscribe.