Transfer Learning for Natural Language Processing you own this product

5 reviews
Paul Azunre
  • July 2021
  • ISBN 9781617297267
  • 272 pages
Included with a Manning Online subscription
  • printed in black & white
  • Available translations: Simplified Chinese
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Build custom NLP models in record time by adapting pre-trained machine learning models to solve specialized problems.

In Transfer Learning for Natural Language Processing you will learn:
  • Fine tuning pretrained models with new domain data
  • Picking the right model to reduce resource usage
  • Transfer learning for neural network architectures
  • Generating text with generative pretrained transformers
  • Cross-lingual transfer learning with BERT
  • Foundations for exploring NLP academic literature

Training deep learning NLP models from scratch is costly, time-consuming, and requires massive amounts of data. In Transfer Learning for Natural Language Processing, DARPA researcher Paul Azunre reveals cutting-edge transfer learning techniques that apply customizable pretrained models to your own NLP architectures. You’ll learn how to use transfer learning to deliver state-of-the-art results for language comprehension, even when working with limited label data. Best of all, you’ll save on training time and computational costs.

about the technology

Build custom NLP models in record time, even with limited datasets! Transfer learning is a machine learning technique for adapting pretrained machine learning models to solve specialized problems. This powerful approach has revolutionized natural language processing, driving improvements in machine translation, business analytics, and natural language generation.

about the book

Transfer Learning for Natural Language Processing teaches you to create powerful NLP solutions quickly by building on existing pretrained models. This instantly useful book provides crystal-clear explanations of the concepts you need to grok transfer learning along with hands-on examples so you can practice your new skills immediately. As you go, you’ll apply state-of-the-art transfer learning methods to create a spam email classifier, a fact checker, and more real-world applications.

what's inside

  • Fine tuning pretrained models with new domain data
  • Picking the right model to reduce resource use
  • Transfer learning for neural network architectures
  • Generating text with pretrained transformers

about the reader

For machine learning engineers and data scientists with some experience in NLP.

about the author

Paul Azunre holds a PhD in Computer Science from MIT and has served as a Principal Investigator on several DARPA research programs.

For anyone looking to dive deep into recent breakthroughs in NLP & transfer learning, this book is for you!

Matthew Sarmiento, Plume Design

Does an excellent job of introducing the techniques and concepts to NLP practitioners.

Marc-Anthony Taylor, Blackshark.ai

Keep this book handy if you want to be good at applied and real-world NLP.

Sayak Paul, PyImageSearch

Good fundamentals of transfer learning for NLP applications. Sets you up for success!

Vamsi Sistla, Data Science & ML Consultant
4.6
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“Great value”
Great Book !
October 4, 2021 by Abdurrahman S. (Paris, France)
“It provides a comprehensive and up-to-date introduction to different techniques employed for the purpose of Transfer Learning in NLP. From basic models like Logistic Regression, to more complex architectures like the Transformer, the author embarks us in an adventure filled with concepts, models, and techniques like multitask learning, domain adaptation, knowledge distillation, embedding, ELMo, RNN, BERT, mBERT, SIMOn, GPT, ULMFiT and ALBERT, to name a few, that become crystal clear at the end of the journey. Moreover, the heavy use of the transformers library allows to grasp concepts and adapt the code to one’s own use cases without unnecessary overhead. Definitely a must read if you want to have innovative insights when facing challenges inherent to Natural Language Processing.”
Verified Buyer
“Great buy”
August 19, 2021 by A Reviewer (US)
“One of the best books on NLP I’ve ever read.”
Verified Buyer
“Great buy”
Very Interesting and Thought Provoking
July 11, 2020 by A Reviewer
“The subject of this book is a more advanced area of Machine Learning, so to get the best out of the book you will need some knowledge of basic machine learning already, and perhaps Natural Language Processing too.
The author takes you through Transfer Learning from the start. I am on the MEAP, so the book is not finished yet, but so far I have found it very interesting and thought provoking. The author said he hopes to convert the examples to TensorFlow V2 before the full publication.”
Verified Buyer
“Good value”
July 23, 2020 by Duncan (IL, United States)
“thus far, quite insightful”
Company Choice
relevant topics, well-explained theory, code that actually works :)
Verified Buyer
“Good ”
May 20, 2020 by - (BE)
“-”
Company Choice
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