Table of Contents
Chapter 1: Learning NLP basics
- Dividing text into sentences
- Dividing sentences into words: tokenization
- Part of speech tagging
- Stemming
- Combining similar words: lemmatization
- Removing stopwords
Chapter 2: Playing with grammar
- Counting nouns: plural and singular nouns
- Getting the dependency parse
- Splitting sentences into clauses
- Extracting noun chunks
- Extracting entities and relations
- Extracting subjects and objects of the sentence
- Finding references: anaphora resolution
Chapter 3: Representing text: capturing semantics
- Putting documents into a bag of words
- Constructing the N-gram model
- Representing texts with TF-IDF
- Using word embeddings
- Training your own embeddings model
- Representing phrases: phrase2vec
- Using BERT instead of word embeddings
- Getting started with semantic search
Chapter 4: Classifying texts
- Getting the dataset and evaluation ready
- Performing rule-based text classification using keywords
- Clustering sentences using K-Means: unsupervised text classification
- Using SVMs for supervised text classification
- Using LSTMs for supervised text classification
Chapter 5: Getting started with information extraction
- Using regular expressions
- Finding similar strings: Levenshtein distance
- Performing named entity recognition using spaCy
- Training your own NER model with spaCy
- Discovering sentiment analysis
- Sentiment for short texts using LSTM: Twitter
- Using BERT for sentiment analysis
Chapter 6: Building chatbots
- LDA topic modeling with sklearn
- LDA topic modeling with gensim
- NMF topic modeling
- K-Means topic modeling with BERT
- Topic modeling of short texts
Chapter 7: Topic modeling
- Building a basic chatbot with keyword matching
- Building a basic Rasa chatbot
- Creating question answer pairs with Rasa
- Creating and visualizing conversation paths with Rasa
- Creating actions for the Rasa chatbot
Chapter 8: Visualizing text data
- Visualizing the dependency parse
- Visualizing parts of speech
- Visualizing NER
- Constructing word clouds
- Visualizing topics