Скачать или смотреть How Transformers Think: The Self-Attention Mechanism Explained Step-by-Step

*Understanding Self-Attention — How Transformers Think Step by Step*

In this video, we break down one of the most revolutionary ideas in deep learning — the *Self-Attention Mechanism* that powers **Transformers, GPT models, and modern AI systems**.

You’ll learn:
What Queries, Keys, and Values really mean 🔍
How the *Scaled Dot-Product Attention* formula works
Why *Masked Attention* matters during training
How to *implement Multi-Head Attention from scratch* in PyTorch
The math and intuition that allow transformers to understand context

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🧩 *Chapters / Timestamps*

00:00 — Introduction: Why Self-Attention Changed AI
01:42 — What Are Queries, Keys, and Values?
04:30 — Scaled Dot-Product Attention Explained
06:55 — Masked Attention: Thinking Step by Step
09:45 — Coding Self-Attention in PyTorch
13:20 — Multi-Head Attention Implementation
17:00 — How Transformers Build Context
20:00 — Real-World Applications (GPT, Gemini, Claude, etc.)
22:15 — Final Thoughts + Next Steps

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💡 *Code & Resources*
GitHub Repo:🔗 https://github.com/cubebarn/Build-your-own...