Applied Text Analysis with Python (O'Reilly)
Thursday, 26 July 2018

This book, subtitled "Enabling Language-Aware Data Products with Machine Learning", presents a data scientist’s approach to building language-aware products with applied machine learning. Authors Benjamin Bengfort, Dr. Rebecca Bilbro and Tony Ojeda demonstrate robust, repeatable, and scalable techniques for text analysis with Python, including contextual and linguistic feature engineering, vectorization, classification, topic modeling, entity resolution, graph analysis, and visual steering. The applied nature of the book means that the authors focus not on the academic nature of linguistics or statistical models, but instead on how to be effective at deploying models trained on text inside of a software application.

 

Authors: Benjamin Bengfort, Dr. Rebecca Bilbro and Tony Ojeda
Publisher: O'Reilly
Date: July 2018
Pages: 332
ISBN: 978-1491963043
Print: 1491963042
Kindle: B07DNKHJL8
Audience: Python developers
Level: Intermediate/Advanced
Category: Artificial Intelligence, Python, Data Science

 

apptext

 

  • Preprocess and vectorize text into high-dimensional feature representations
  • Perform document classification and topic modeling
  • Steer the model selection process with visual diagnostics
  • Extract key phrases, named entities, and graph structures to reason about data in text
  • Build a dialog framework to enable chatbots and language-driven interaction
  • Use Spark to scale processing power and neural networks to scale model complexity.

For recommendations of Python books see Books for Pythonistas and Python Books For Beginners in our Programmer's Bookshelf section.

For more Book Watch just click.

Book Watch is I Programmer's listing of new books and is compiled using publishers' publicity material. It is not to be read as a review where we provide an independent assessment. Some, but by no means all, of the books in Book Watch are eventually reviewed.

To have new titles included in Book Watch contact  BookWatch@i-programmer.info

Follow @bookwatchiprog on Twitter or subscribe to I Programmer's Books RSS feed for each day's new addition to Book Watch and for new reviews.

 

 

Banner
 


Classic Computer Science Problems in Python

Author: David Kopec
Publisher: Manning
Date: March 2019
Pages: 224
ISBN: 978-1617295980
Print: 1617295981
Kindle: ‎ ‎ B09782BT4Q
Level: Intermediate
Audience: Python developers
Category: Python
Rating: 4
Reviewer: Mike James
Classic algorithms in Python - the world's favourite language.



R for the Rest of Us

Author: David Keyes
Publisher: No Starch Press
Date: June 2024
Pages: 256
ISBN: 978-1718503328
Print: 1718503326
Kindle: B0CD3GV46N
Audience: Beginners interested in R
Rating: 3
Reviewer: Mike James
Well I'm certainly the "rest of us" - what about you?


More Reviews