Natural Language Processing and Computational Linguistics
Discover how you can perform your own modern text analysis, to make predictions, create inferences, and gain insights about the data around you today. Learn how to harness the powerful Python ecosystem and tools such as spaCy and Gensim to perform natural language processing, and computational linguistics algorithms.
Offered by
Difficulty Level
Intermediate
Completion Time
10h12m
Language
English
About Book
Who Is This Book For?
This book is for you if you want to dive in, hands-first, into the interesting world of text analysis and NLP, and you're ready to work with the rich Python ecosystem of tools and datasets waiting for you!
Natural Language Processing and Computational Linguistics
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 10h12m total length
What is Text Analysis?
Python Tips for Text Analysis
spaCy’s Language Models
Gensim – Vectorizing text and transformations and n-grams
POS-Tagging and its Applications
NER-Tagging and its Applications
Dependency Parsing
Top Models
Advanced Topic Modelling
Clustering and Classifying Text
Similarity Queries and Summarization
Word2Vec, Doc2Vec and Gensim
Deep Learning for text
Keras and spaCy for Deep Learning
Sentiment Analysis and ChatBots
Related Resources
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