---
product_id: 285934400
title: "Transformers for Natural Language Processing: Build innovative deep neural network architectures for NLP with Python, PyTorch, TensorFlow, BERT, RoBERTa, and more"
price: "B/.341"
currency: PAB
in_stock: true
reviews_count: 5
url: https://www.desertcart.com.pa/products/285934400-transformers-for-natural-language-processing-build-innovative-deep-neural-network
store_origin: PA
region: Panama
---

# Transformers for Natural Language Processing: Build innovative deep neural network architectures for NLP with Python, PyTorch, TensorFlow, BERT, RoBERTa, and more

**Price:** B/.341
**Availability:** ✅ In Stock

## Quick Answers

- **What is this?** Transformers for Natural Language Processing: Build innovative deep neural network architectures for NLP with Python, PyTorch, TensorFlow, BERT, RoBERTa, and more
- **How much does it cost?** B/.341 with free shipping
- **Is it available?** Yes, in stock and ready to ship
- **Where can I buy it?** [www.desertcart.com.pa](https://www.desertcart.com.pa/products/285934400-transformers-for-natural-language-processing-build-innovative-deep-neural-network)

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## Description

Buy Transformers for Natural Language Processing: Build innovative deep neural network architectures for NLP with Python, PyTorch, TensorFlow, BERT, RoBERTa, and more by Rothman, Denis online on desertcart.ae at best prices. ✓ Fast and free shipping ✓ free returns ✓ cash on delivery available on eligible purchase.

Review: El autor, muy reputado, explica de forma muy sencilla las bases y aplicaciones de Transformers
Review: A well intended hands-on book for NLP enthusiasts; however, when it comes to explaining the core concepts the language barrier is quite evident and the explanations are brief. For example, the author mentions about paying extra focus on the chapter about transformers, which ironically is brief and difficult to digest without referring to the nice free-of-cost references listed at the end of the chapter and in the github notebooks. This holds for the following chapters as well. Additionally, there are quite a few errors in the text. A bit more proofreading is what one could expect for the price you pay. All in all a decent attempt with an overview of transformers, transformer-based architectures and its applications. However, if you are looking for step-by-step conceptual explanations about transformers and their variations this is NOT your go to reference. Personally, I would recommend Getting started with Google BERT by Sudharsan Ravichandiran. On the other hand, if you are is looking for clear steps to set up your first transformers notebook project, this could be a resource to refer to. On a totally different note, if still interested in the book, the publisher offers, both, print + ebook (immediate access) for a lower price of about 29 euros.

## Technical Specifications

| Specification | Value |
|---------------|-------|
| Customer reviews | 4.2 4.2 out of 5 stars (66) |
| Dimensions  | 19.05 x 2.21 x 23.5 cm |
| Edition  | Standard Edition |
| ISBN-10  | 1800565798 |
| ISBN-13  | 978-1800565791 |
| Item weight  | 210 g |
| Language  | English |
| Print length  | 384 pages |
| Publication date  | 28 January 2021 |
| Publisher  | Packt Publishing |

## Images

![Transformers for Natural Language Processing: Build innovative deep neural network architectures for NLP with Python, PyTorch, TensorFlow, BERT, RoBERTa, and more - Image 1](https://m.media-amazon.com/images/I/71U4XMjm1QL.jpg)

## Customer Reviews

### ⭐⭐⭐⭐⭐ Review
*by J***O on 27 June 2021*

El autor, muy reputado, explica de forma muy sencilla las bases y aplicaciones de Transformers

### ⭐⭐ Review
*by A***R on 9 March 2021*

A well intended hands-on book for NLP enthusiasts; however, when it comes to explaining the core concepts the language barrier is quite evident and the explanations are brief. For example, the author mentions about paying extra focus on the chapter about transformers, which ironically is brief and difficult to digest without referring to the nice free-of-cost references listed at the end of the chapter and in the github notebooks. This holds for the following chapters as well. Additionally, there are quite a few errors in the text. A bit more proofreading is what one could expect for the price you pay. All in all a decent attempt with an overview of transformers, transformer-based architectures and its applications. However, if you are looking for step-by-step conceptual explanations about transformers and their variations this is NOT your go to reference. Personally, I would recommend Getting started with Google BERT by Sudharsan Ravichandiran. On the other hand, if you are is looking for clear steps to set up your first transformers notebook project, this could be a resource to refer to. On a totally different note, if still interested in the book, the publisher offers, both, print + ebook (immediate access) for a lower price of about 29 euros.

### ⭐⭐⭐⭐⭐ Review
*by X***Y on 24 February 2021*

This book is a comprehensive reference on Transformers, the new technologies used in natural language processing. The book covers all the mathematics and architectures. It goes in details over HuggingFaces, Bert, Roberta, GPT2 , GPT3, T5, and many more. It is recommended if you want to have an handson understanding on the technologies that took natural language processing by Storm and made things like CNN and ever Menon absolute obsolete. Very much liked chapter 4 with the challenges observed in modern nlp. definitely recommend the book. 5 Stars, also because updated to 2021.

## Frequently Bought Together

- Transformers for Natural Language Processing: Build innovative deep neural network architectures for NLP with Python, PyTorch, TensorFlow, BERT, RoBERTa, and more
- Getting Started with Google BERT: Build and train state-of-the-art natural language processing models using BERT

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*Product available on Desertcart Panama*
*Store origin: PA*
*Last updated: 2026-05-06*