About the Book

Preliminary Table of Content

NLTK

1. Introduction to NLTK
2. Lemmatising and stemming words
3. Training a simple occurrence based tagger
4. Bigrams and Trigrams
5. Finding collocations

Scikit-Learn

1. Text Classification with NaiveBayes
2. Text Clustering
3. Displaying text in 2D with t-SNE
4. Building a POS Tagger using a SVM model
5. Building a NER using CRFSuite
6. Building a POS tagger using Pomegranate

Gensim

1. Building an LDA Topic model
2. Extracting collocations with the Phrase model
3. Training a Word2Vec model
4. Text summarisation with TextRank

spaCy

1. Introduction to spaCy
2. Visualising dependency trees
3. Training your NER
4. Adding new language support

Keras

1. Building a DNN for Sentiment Analysis
2. Building an RNN for sentiment Analysis
3. Building an RNN for POS Tagging
4. Transfer Learning using pretrained word vectors
5. Headline generation

About the Author

Bogdan Ivanov

@swampsio