Applied Natural Language Processing in the Enterprise: Teaching Machines to Read, Write, and Understand

by Ankur A Patel, Ajay Arasanipalai

NLP has exploded in popularity over the last few years. But while Google, Facebook, OpenAI, and others continue to release larger language models, many teams still struggle with building NLP applications that live up to the hype. This hands-on guide helps you get up to speed on the latest and most promising trends in NLP. With a basic understanding of machine learning and some Python experience, you'll learn how to build, train, and deploy models for real-world applications in your organization. Authors Ankur Patel and Ajay Uppili Arasanipalai guide you through the process using code and examples that highlight the best practices in modern NLP.

Genres: Programming

333 pages, Paperback

Published June 15, 2021

Reviews

[Petr Lorenc · Rating 2 out of 5]

There is good part about Transformer's model but the rest is below average.

[Matias Grioni · Rating 2 out of 5]

* Poorly organized (saying "but we'll get to that later" several times throughout the book may be a sign things are not properly ordered)
* The evolution of models to transformers and the general idea of what each of these models is, comes after the chapters on them??
* Too many specifics for certain platforms and services. Large chunks of the book are essentially tutorials more adequate for a technical wikihow. For Christ's sake it shows how to make a curl request with Databricks, Curl, and, Python. I would thing just saying you exposed a rest endpoint is sufficient.

Anyway, not sure who this book could actually be for. The practical guides are relatively simple and can be easily stumbled through with online resources while the technical information is so laughably glossed over that you have to both be an expert (at having context about different model types) and a novice (on simple programming) for this to be useful.

A few summary chapters cut through and are actually useful and give this more than 1 star.