oreilly-japan/deep-learning-from-scratch-2 resource

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1249 stars · 794 forks observed · 2026-08-28

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

Companion source code repository for the O'Reilly Japan book 'Deep Learning from Scratch 2: Natural Language Processing' (2018). It contains per-chapter Python/NumPy implementations of NLP deep learning techniques such as word2vec, RNN/LSTM language models, and attention mechanisms.

Use cases

• learn deep learning for NLP from scratch
• implement word2vec without frameworks
• understand RNN and LSTM internals
• study attention mechanism code
• follow a deep learning textbook with runnable code

When to choose

• you are reading the book and want its official code
• you want framework-free NumPy implementations to learn fundamentals
• you prefer minimal dependencies (NumPy/Matplotlib)

When to avoid

• you need a production-ready NLP or deep learning library
• you want GPU-optimized training at scale (CuPy is optional and limited)
• you need maintained, feature-rich tooling rather than educational code

Facets

learning-resource · maturity maintenance

deep-learning nlp machine-learning deep-learning education tutorials python cross-platform book-companion-code word2vec rnn attention numpy-only japanese-book natural-language-processing

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