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Advanced Natural Language Processing with TensorFlow 2
Advanced Natural Language Processing with TensorFlow 2

Advanced Natural Language Processing with TensorFlow 2: Build effective real-world NLP applications using NER, RNNs, seq2seq models, Transformers, and more

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Profile Icon Ashish Bansal Profile Icon Mullen
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£9.99 per month
Full star icon Full star icon Full star icon Full star icon Half star icon 4.8 (35 Ratings)
Paperback Feb 2021 380 pages 1st Edition
eBook
£26.99
Paperback
£32.99
Subscription
Free Trial
Renews at £9.99p/m
Arrow left icon
Profile Icon Ashish Bansal Profile Icon Mullen
Arrow right icon
£9.99 per month
Full star icon Full star icon Full star icon Full star icon Half star icon 4.8 (35 Ratings)
Paperback Feb 2021 380 pages 1st Edition
eBook
£26.99
Paperback
£32.99
Subscription
Free Trial
Renews at £9.99p/m
eBook
£26.99
Paperback
£32.99
Subscription
Free Trial
Renews at £9.99p/m

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Key benefits

  • Apply deep learning algorithms and techniques such as BiLSTMS, CRFs, BPE and more using TensorFlow 2
  • Explore applications like text generation, summarization, weakly supervised labelling and more
  • Read cutting edge material with seminal papers provided in the GitHub repository with full working code

Description

Recently, there have been tremendous advances in NLP, and we are now moving from research labs into practical applications. This book comes with a perfect blend of both the theoretical and practical aspects of trending and complex NLP techniques. The book is focused on innovative applications in the field of NLP, language generation, and dialogue systems. It helps you apply the concepts of pre-processing text using techniques such as tokenization, parts of speech tagging, and lemmatization using popular libraries such as Stanford NLP and SpaCy. You will build Named Entity Recognition (NER) from scratch using Conditional Random Fields and Viterbi Decoding on top of RNNs. The book covers key emerging areas such as generating text for use in sentence completion and text summarization, bridging images and text by generating captions for images, and managing dialogue aspects of chatbots. You will learn how to apply transfer learning and fine-tuning using TensorFlow 2. Further, it covers practical techniques that can simplify the labelling of textual data. The book also has a working code that is adaptable to your use cases for each tech piece. By the end of the book, you will have an advanced knowledge of the tools, techniques and deep learning architecture used to solve complex NLP problems.

Who is this book for?

This is not an introductory book and assumes the reader is familiar with basics of NLP and has fundamental Python skills, as well as basic knowledge of machine learning and undergraduate-level calculus and linear algebra. The readers who can benefit the most from this book include intermediate ML developers who are familiar with the basics of supervised learning and deep learning techniques and professionals who already use TensorFlow/Python for purposes such as data science, ML, research, analysis, etc.

What you will learn

  • Grasp important pre-steps in building NLP applications like POS tagging
  • Use transfer and weakly supervised learning using libraries like Snorkel
  • Do sentiment analysis using BERT
  • Apply encoder-decoder NN architectures and beam search for summarizing texts
  • Use Transformer models with attention to bring images and text together
  • Build apps that generate captions and answer questions about images using custom Transformers
  • Use advanced TensorFlow techniques like learning rate annealing, custom layers, and custom loss functions to build the latest DeepNLP models

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Feb 04, 2021
Length: 380 pages
Edition : 1st
Language : English
ISBN-13 : 9781800200937
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Product Details

Publication date : Feb 04, 2021
Length: 380 pages
Edition : 1st
Language : English
ISBN-13 : 9781800200937
Category :
Languages :
Tools :

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Frequently bought together


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Total £ 142.97
Transformers for Natural Language Processing
£67.99
Python Natural Language Processing Cookbook
£41.99
Advanced Natural Language Processing with TensorFlow 2
£32.99
Total £ 142.97 Stars icon
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Customer reviews

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Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.8
(35 Ratings)
5 star 88.6%
4 star 5.7%
3 star 2.9%
2 star 2.9%
1 star 0%
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Manu Goyal Jun 02, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
A practical book for techniques in NLP.The best part is the sample code included with the book that makes it easy to test.A word of caution - not very suitable for beginners.Overall 5*!
Amazon Verified review Amazon
Marleen Mar 28, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I believe that last year, NLP was the fastest growing area in Machine Learning and many new techniques were published in a multitude of papers. The One-Hot-Encoding times are definitely over by now and this book will bring you up to speed on whats out there. It is very hard to keep track of all the new developments and therefore I very much appreciate that this book has a bit of all and that it will help you staying up to date (for now) and applies various models such that one can see how they work. Additionally, given the low(er) price range a must have - in my opinion.
Amazon Verified review Amazon
Mrinal Sinha Apr 01, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I have been reading books and articles related to NLP since long. I found this book by Ashish Bansal is perfect combination of theory behind NLP and practical application. Examples and sample code help you to understand the concept with more clarity. Different concepts are structured and presented in the form where it is easy to grasp. I recommend this book for all NLP enthusiast .
Amazon Verified review Amazon
Anshul Kulshrestha, Data Science Engineer at Google Feb 24, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
The book is a very good mix of both ML theory and practical examples.The book covers concepts that can be very useful in modern business applications like autocomplete, text summarization and chatbot design.
Amazon Verified review Amazon
HouseofNirvan Mar 26, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Ashish makes it a point to make sure the book caters to both novice and experienced audience. He starts by laying a foundation of NLP by covering topics like stemming, tokenization, etc. He also provides code snippets and the necessary state of the art libraries that are being used in the industry like Stanford CoreNLP, BERT, HuggingFace, etc. This book strikes a good balance between practical and theory. As a learner it is important for me to be able to try things myself. The availability of code snippets makes it easy to follow and code in a Collab notebook. The book also pushes one to deep dive into how preprocessing should be done for Japanese and German which are much harder as compared to English.Looking forward to future topics like Transformers, GPT-2 and BERT and looking ahead to building a Chatbot
Amazon Verified review Amazon
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