This book will take you through a range of techniques for text processing, from basics such as parsing the parts of speech to complex topics such as topic modeling, text classification, and visualization. Zhenya Antić shows how to solve real-world NLP problems, such as dependency parsing, information extraction, topic modeling, and text data visualization.

<ASIN:1838987312>

The recipes in the book cover different ways of representing the semantics using bag-of-words, TF-IDF, word embeddings, and BERT, and develop skills for text classification using keywords, SVMs, LSTMs, and other techniques. The book also shows how to develop chatbots using NLTK and Rasa and visualize text data.

Author: Zhenya Antić
Publisher: Packt
Date: March 2021
Pages: 284
ISBN: 978-1838987312
Print: 1838987312
Kindle: B08SRDF78Y
Audience: Python developers interested in language processing
Level: Intermediate/Advanced
Category: Artificial Intelligence

• Analyze varying complexities of text using popular Python packages such as NLTK, spaCy, sklearn, and gensim
• Implement common and not-so-common linguistic processing tasks using Python libraries
• Overcome the common challenges faced while implementing NLP pipelines

For recommendations of books on Artificial Intelligence see AI Books To Inspire You in our Programmer's Bookshelf section.

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