Check order status

Become part of a community of book lovers from all over the world and get access to a whole bunch of benefits. Create an account for free

Austrian Post 5.49 € DPD courier 3.99 € DPD point 2.99 €

Contact

How to shop

Help

My account

▸ Empty :-(

Transfer Learning for Natural Processing

Name: Transfer Learning for Natural Processing
Brand: Manning Publications
SKU: 35456146
Price: 56.09 EUR
Availability: InStock
Author: Paul Azunre
ISBN: 9781617297267

Paul Azunre

Language

English

Book Paperback

Libristo code: 35456146

Publishers Manning Publications, August 2021

Building and training deep learning models from scratch is costly, time-consuming, and requires ma... Full description

Libristo code: 35456146

137 b

56.09 € VAT included

50 % chance We search the world When will I receive my book?

Delivery to Austria

30-day return policy

Customers also purchased

Jod leczy Lynne Farrow

Paperback

11.79 €

Schritte International 1 KB+AB mit CD Daniela Niebisch

Paperback

24.00 €

Einheit und Vielfalt der Rechtstheorie. Robert Weimar

Hardback

120.89 €

Lextra - Deutsch als Fremdsprache - Grund- und Aufbauwortschatz nach Themen - A1-B2 Erwin Tschirner

Paperback

23.99 €

Die Sprachenhilfe für den Fahrer Sigurd Ehringer

Paperback

18.19 €

Módne kočky - čas na líčenie

Paperback

4.09 €

Mity greckie 6 Chimera Nathaniel Hawthorne

Paperback

9.79 €

WOHLTEMP KLAVIER I Johann Sebastian Bach

Sheet music

26.50 €

Poupon la peste - Tome 02 Christian Binet

Hardback

17.19 €

Deutsche Marchen Seit Grimm V1 (1922) Paul Zaunert

Paperback

38.69 €

Building and training deep learning models from scratch is costly, time-consuming, and requires massive amounts of data. To address this concern, cutting-edge transfer learning techniques enable you to start with pretrained models you can tweak to meet your exact needs. In Transfer Learning for Natural Language Processing, DARPA researcher Paul Azunre takes you hands-on with customizing these open source resources for your own NLP architectures. You’ll learn how to use transfer learning to deliver state-of-the-art results even when working with limited label data, all while saving on training time and computational costs.

about the technology

Transfer learning enables machine learning models to be initialized with existing prior knowledge. Initially pioneered in computer vision, transfer learning techniques have been revolutionising Natural Language Processing with big reductions in the training time and computation power needed for a model to start delivering results. Emerging pretrained language models such as ELMo and BERT have opened up new possibilities for NLP developers working in machine translation, semantic analysis, business analytics, and natural language generation.

about the book

Transfer Learning for Natural Language Processing is a practical primer to transfer learning techniques capable of delivering huge improvements to your NLP models. Written by DARPA researcher Paul Azunre, this practical book gets you up to speed with the relevant ML concepts before diving into the cutting-edge advances that are defining the future of NLP. You’ll learn how to adapt existing state-of-the art models into real-world applications, including building a spam email classifier, a movie review sentiment analyzer, an automated fact checker, a question-answering system and a translation system for low-resource languages.

what''s inside

Fine tuning pretrained models with new domain data
Picking the right model to reduce resource usage
Transfer learning for neural network architectures
Foundations for exploring NLP academic literature

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. He founded Algorine Inc., a Research Lab dedicated to advancing AI/ML and identifying scenarios where they can have a significant social impact. Paul also co-founded Ghana NLP, an open source initiative focused using NLP and Transfer Learning with Ghanaian and other low-resource languages. He frequently contributes to major peer-reviewed international research journals and serves as a program committee member at top conferences in the field.