How Machines Learn — Supervised, Unsupervised & Reinforcement Learning Explained | Master AI & ML E3

How do machines actually learn? In this episode we break down the three fundamental ML training approaches — supervised, unsupervised, and reinforcement learning — plus self-supervised learning, the technique behind every major language model.

In this episode:
→ Supervised learning — labeled data, error correction, real examples
→ Unsupervised learning — finding hidden structure without labels
→ Reinforcement learning — reward signals, policies, AlphaGo, RLHF
→ Self-supervised learning — how GPT, Claude, and Llama are actually trained
→ A decision framework: which approach to use and when

This is Episode 3 of Master AI & Machine Learning — a 35-episode course for developers, analysts, and technical professionals.

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📋 FULL COURSE PLAYLIST]
⬅ Ep 02 — AI vs ML vs Deep Learning
➡ Ep 04 — Real-world AI you already use
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⏱ TIMESTAMPS
00:00 — Hook
00:25 — Supervised learning
02:30 — Unsupervised learning
04:30 — Reinforcement learning & RLHF
06:30 — Self-supervised learning (how LLMs are trained)
07:30 — Choosing the right approach
08:30 — Next episode & CTA

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Series of Thoughts · Presented by TechnovativeAI

#MachineLearning #SupervisedLearning #ReinforcementLearning #UnsupervisedLearning #RLHF #LearnAI #TechnovativeAI #SeriesOfThoughts #MLtutorial #DeepLearning