Chapter 1. Packets of thought (NLP overview)
Chapter 2. Build your vocabulary (word tokenization)
Chapter 3. Math with words (TF-IDF vectors)
Chapter 4. Finding meaning in word counts (semantic analysis)
2. Deeper learning (neural networks)
Chapter 5. Baby steps with neural networks (perceptrons and backpropagation)
Chapter 6. Reasoning with word vectors (Word2vec)
Chapter 7. Getting words in order with convolutional neural networks (CNNs)
Chapter 8. Loopy (recurrent) neural networks (RNNs)
Chapter 9. Improving retention with long short-term memory networks
3. Getting real (real-world NLP challenges)
Chapter 11. Information extraction (named entity extraction and question answering)
Chapter 12. Getting chatty (dialog engines)
Chapter 13. Scaling up (optimization, parallelization, and batch processing)
B. Playful Python and regular expressions
C. Vectors and matrices (linear algebra fundamentals)