What it does

This repo holds worked solutions for all five assignments plus the final project from Stanford’s CS224n (Winter 2019), the well-known “Natural Language Processing with Deep Learning” course. You’ll find Python code for the coding portions and Markdown write-ups for the theory questions, organized week by week alongside reading notes.

The interesting bit

The author treats it as a living document. A 2019 update confesses that “many faults or incorrect habits” surfaced after a year in industry and lab work, and commits to reviewing old code gradually. That transparency is rarer than you’d think in solution repos.

Key highlights

• Covers the full arc: word vectors (Word2Vec, GloVe), dependency parsing, RNNs/LSTMs, sequence-to-sequence with attention, and a final machine-comprehension project
• Written solutions are in English Markdown, not just scanned PDFs
• Includes supplementary notes on tricky PyTorch utilities like pack_padded_sequence
• Links to the official lecture videos and course page for context
• Author later spawned a broader “learn NLP from scratch again” project based on Jurafsky & Martin’s textbook

Caveats

• Some early solutions may still contain the admitted “faults”; the author is reviewing gradually
• Final project section is lighter on detail than the weekly assignments
• Sparse commit history suggests this was maintained in bursts

Verdict

Grab this if you’re self-studying CS224n and want to sanity-check your own work, or if you prefer reading solutions in plain Markdown over forum threads. Skip it if you need polished, peer-reviewed reference implementations — this is a study journal, not a textbook supplement.