Amazon.com.au:Customer reviews: Practical Natural Language Processing: A Comprehensive Guide to Building Real-World NLP Systems

There are 0 reviews and 1 rating from Australia

M.Soczka

This book is literally falling apart. Page by page.

Reviewed in the United Kingdom on 12 September 2020

First copy started loosing pages from the first reading session and continued thereafter.
Then I requested a replacement and same story happened again.
Much as I am focused on the content of the book the form in which it comes is also important.
You can't sell books that are loosing pages so easily.

3 people found this helpful

Abel

Quality is really bad

Reviewed in Germany on 6 April 2022

Verified Purchase

This is the first time I got a book which cover is correct, but the content is completely wrong.
How is it possible?
The book I got was "Infrastructure as Code", see Photo., but the cover says Practical Natural Language Processing.
Usually, I wouldn't give a bad review, but I read that many users complained about the book's quality. Well, I wouldn't suggest to buy the book until they fix their quality issues.

2 people found this helpful

Anish Shah

Meh! Not colour edition

Reviewed in Canada on 15 December 2020

Verified Purchase

B/W edition...the feel of the pages of an authentic o rielly publication is duly missing..

Jiawei

I’d definitely recommend but...

Reviewed in Spain on 26 August 2020

Verified Purchase

Love the book but not sure why it’s in black and white and the images are so blurry..

One person found this helpful

Chris

Qualité d'impression décevante

Reviewed in France on 25 October 2020

Verified Purchase

Très déçu de la qualité d'impression de ce livre vendu et expédié par Amazon. En effet, les images sont à peine visibles (voir photo 1) en comparaison à celles disponibles sur les extraits publiques du livre (voir photo 2). Cela sans parler de l'épaisseur de pages et de la sensation globale de n'avoir pas un produit O'Reilly sur la main. Retour et remboursement demandé.

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marvin

outdated and very shallow

Reviewed in France on 6 January 2021

Verified Purchase

It covers a lot of subjects but very superficially, and uses almost exclusively outdated techniques.
Still ok if you know absolutely nothing about the subject but it's nowhere wear a practical book, especially if you're looking for business applications.

One person found this helpful

This is not a bad book BUT...

Reviewed in the United States on 29 January 2021

Verified Purchase

... the word "practical" in the title might make you think about the word "applied", as in code. That was what I was expecting. This is a great book to give a manager to read about NLP. They will understand things at a high level after reading it. However it just does not get the job done for someone like myself looking to apply this knowledge.

13 people found this helpful

Matthew Emerick

Foundational to Learning NLP

Reviewed in the United States on 9 March 2021

Verified Purchase

About This Book
This was a highly regarded book when it came out in the summer of 2020, and I can see why. It's the generalist's guide to NLP, a high-level overview of the entire field. If you want to learn about natural language processing, this is where you start. There are books to read after this one, but this is your foundation.

Who Is This For?
The authors intent this book to be for anyone who is interested in or working in the field. However, they also have a list of prerequisites they want you to have to gain the maximum value from the book: an intermediate level of Python, knowledge of the general software development life cycle, a basic knowledge of machine learning, and some general knowledge of what NLP is. I can see where these can be useful, but I also agree with the authors that these are not completely necessary.

Why Was This Written?
The authors wrote this book to fill a perceived gap between what previous books offered versus what they think is required for working with natural language in production. From what I have seen from other books, I can agree.

Organization
The macrostructure of this book is well thought out and is broken up into four parts: foundations, essentials, applied, and bringing it all together. I really like these sections and how they include a map of reading order in the preface. This is useful when you already have a little bit of knowledge and want to see how best to skip around without missing anything.

Within the chapters, each one is different, but all end with a wrapping up section to summarize the chapter and give all the references. Having a summary at the end is great for helping the reader retain the information they just read. I never understood why some technical books leave this out.

Did This Book Succeed?
Yes, very much so. This is a foundational book for anyone learning natural language processing that paves the way for more detailed books when you want to drill down and specialize. It's well laid out and easy to navigate. This should be on the bookshelf of anyone working in artificial intelligence.

Rating and Final Thoughts
This book is step one to learning natural language processing and has earned all of the accolades it has been given. Buy this book and read through it to have a thorough understanding of the field without getting stuck in the details.

I give this book a 5 out of 5. This should be in your library.

7 people found this helpful

Siddharth Narayanan

Excellent resource for building production level NLP pipelines!

Reviewed in the United States on 22 December 2020

Verified Purchase

First, a little bit about my background. I have been working in silicon valley for the past decade for a smattering of companies (both big and small). I am the typical software engineer who decided to switch to machine learning and have been building recommendation systems for the last 5 years. In fact, NLP is front and center in my current company (Hint: it is where you probably read most of your data science articles on the web) and this is where I found that the utility of the book shines through.

What really stood out to me is how well this book has been laid out coaxing a beginner through various aspects of language and then leading them through the complex technical aspects with tremendous lucidity. The code samples serve to further reinforce these concepts as the authors seem to understand that the best way to really learn something is by doing. In my experience reading articles and books on ML/NLP, there are a lot of assumptions about the reader. I found it refreshing that this book makes no such assumptions. How many books do you know that actually explain what an "embedding" is? That being said, one of the major strengths of this book is that it effortlessly combines theoretical aspects with practical advice on building real world NLP systems. It is evident that the authors have first hand experience in building scalable machine learning systems and have thoroughly addressed many of these challenges in the book.

The one issue I did find while reading this book is that the images were not sharp enough and I had sometimes squint to read what was written. All-in-all I think this is book does a terrific job at breaking down complex technical aspects of NLP and is also a very handy reference book for experts to jog their memory about key concepts. I also found it extremely useful for interviews since a lot of the concepts are laid out in a very easy to understand fashion.

5 people found this helpful

Paul S

Good for beginners

Reviewed in the United States on 1 July 2020

Verified Purchase

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Loved the book! Having worked at Fortune 100 and having a Ph.D. from a top school, this was still valuable for me to get a high-level overview of NLP.

I liked that this book extensively covered important and practical domains such as e-commerce and healthcare, which I don’t even remember seeing in currently available books. Especially I appreciated their “pipeline” approach to solving a problem with informative diagrams. And finally, I really enjoyed the plentiful references in the book that cover both depth and breadth.

I am going for a five star as the book stands to what it promised! Only con: I wish they could fix the formatting of the references in the kindle version.

8 people found this helpful

5 star		62%
4 star		20%
3 star		6%
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1 star		7%

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