Preview "Blueprints for Text Analytics Using Python" in a new window.

Blueprints for Text Analytics Using Python

Authors

Book Description

Turning text into valuable information is essential for businesses looking to gain a competitive advantage. With recent improvements in natural language processing (NLP), users now have many options for solving complex challenges. But it's not always clear which NLP tools or libraries would work for a business's needs, or which techniques you should use and in what order.

This practical book provides data scientists and developers with blueprints for best practice solutions to common tasks in text analytics and natural language processing. Authors Jens Albrecht, Sidharth Ramachandran, and Christian Winkler provide real-world case studies and detailed code examples in Python to help you get started quickly.

Extract data from APIs and web pagesPrepare textual data for statistical analysis and machine learningUse machine learning for classification, topic modeling, and summarizationExplain AI models and classification resultsExplore and visualize semantic similarities with word embeddingsIdentify customer sentiment in product reviewsCreate a knowledge graph based on named entities and their relations

In The Press

About the Author

Read on Your Favourite Devices

to find out more

Ebook Permissions

to find out more

About this Ebook

File formats
This ebook is available in:
The publisher has not yet supplied format information.
Pre-order formats shown are based on publisher intent and may change before release.
File sizes shown are an approximation. The actual download size will vary based on the application you use to read the book.
Publisher
Published
; Copyright:
ISBNs
Title
Series
Author
;
Edition
Imprint
Language
Number of Pages
Page count shown is an approximation provided by the publisher. The actual page count will vary based on various factors such as your device's screen size and font-size.