Miraclelucy/dive_into_deep_learning resource

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3074 stars · 504 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A collection of Python study notes for Mu Li's 'Dive into Deep Learning' course, rewritten from the original Jupyter notebooks into standalone .py files using PyCharm and PyTorch. It covers fundamentals through CNNs with runnable implementations of linear regression, softmax regression, MLPs, and convolutional networks.

Use cases

• learn deep learning with pytorch following the d2l course
• find pytorch implementations of linear regression from scratch
• study softmax regression and mlp examples in python
• understand autograd and linear algebra basics for deep learning
• get runnable py scripts instead of jupyter notebooks for d2l
• prepare for kaggle house price prediction with deep learning

When to choose

• you are following Mu Li's Dive into Deep Learning course and prefer .py files over notebooks
• you want from-scratch PyTorch implementations of classic neural network concepts
• you read Chinese and want course-aligned study notes

When to avoid

• you need a production deep learning framework or library
• you want English-language materials or the official d2l.ai content
• you need maintained, licensed code for a real project

Facets

learning-resource · maturity maintenance

deep-learning machine-learning developer-tools deep-learning machine-learning tutorials education python pytorch d2l course-notes study-notes chinese linear-regression cnn mlp

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