๐Ÿงญ Roadmap โ€บ 04 ยท Build Language Models โ€บ Pretraining โ€บ Gradient Descent
โ† Pretraining

Gradient Descent

๐Ÿ”ด Core
Area04 ยท Build Language Models
TopicPretraining
Topic priority๐Ÿ”ด MUST
Subtopic9 of 11
Study this using 6 phases
๐Ÿง  01 Understand

What is Gradient Descent? Why does it exist? Where does it appear in Pretraining?

๐Ÿ‘๏ธ 02 Visualize

Draw or describe a visual model of Gradient Descent. What does it look like conceptually?

โœ๏ธ 03 Calculate

Work through a concrete manual example of Gradient Descent with real numbers or pseudocode.

๐Ÿ’ป 04 Code

Implement Gradient Descent from scratch in Python. Keep it minimal โ€” just enough to see it work.

โš–๏ธ 06 Compare

How is Gradient Descent different from related concepts in Pretraining? What are the trade-offs?

๐Ÿ—ฃ๏ธ 07 Explain

Explain Gradient Descent in plain language using an analogy. Could a non-expert follow it?

โ† Backpropagation Learning Rate โ†’
๐Ÿงช
RASL Pull ยท S-05 Pulled because: how do checkpoints work โ€” what does save/restore mean?
๐Ÿ”จ M-06 train.py checkpoints ๐Ÿ” checkpoint pattern = RASL state snapshots โ†’ return to train.py ๐Ÿ“‹ full plan โ†’
โ†‘ All subtopics in Pretraining
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