TensorFlow 1.2 study notes from a Chinese ML student
A structured learning diary for Google's Udacity deep-learning course, mixing Mandarin explanations with runnable code.

What it does
This repo is a Chinese-language companion to Google’s Udacity deep-learning course (UD730), rebuilt for TensorFlow 1.2. It walks through four lessons — from logistic regression up through CNNs and RNNs — with both theory notes and practice markdown files. The author also links to side repos for NumPy, matplotlib, sklearn, and a “watermelon book” (周志华’s ML classic) concept list.
The interesting bit
The candor. The README opens with “frameworks are tools” and ends with a 400×400 QR code begging donations for a quad-1080Ti rig. That tension — serious pedagogy meets broke grad student — gives the project more personality than most MOOC clones.
Key highlights
- Covers four lesson arcs: logistic classification → deep nets → convnets → sequence models
- Each lesson pairs a theory note with a “practical” (实践) exercise file
- Includes a TensorFlow install “pitfall log” (踩坑日志) — useful for the era
- Links to video and subtitle downloads for the Udacity course
- CC-BY-NC-ND licensed
Caveats
- Frozen in time: “refactored for TensorFlow 1.2” means pre-eager, pre-Keras-integration TF
- Appendix notes (NumPy, matplotlib, sklearn) marked “待完善” — unfinished
- No code visible in the README; actual notebooks/scripts live in subdirectories
Verdict
Worth a look if you’re a Mandarin speaker trying to make sense of legacy TensorFlow tutorials, or curious how self-directed ML education looked in China circa 2017. Skip if you need modern TF/PyTorch or English-first explanations.