Picture 1 of 5

Stock photo

Transformers for Machine Learning: A Deep Dive by Uday Kamath Fast Shipping.... - Picture 1 of 5

Transformers for Machine Learning: A Deep Dive by Uday Kamath Fast Shipping.... - Picture 2 of 5

Transformers for Machine Learning: A Deep Dive by Uday Kamath Fast Shipping.... - Picture 3 of 5

Transformers for Machine Learning: A Deep Dive by Uday Kamath Fast Shipping.... - Picture 4 of 5

Transformers for Machine Learning: A Deep Dive by Uday Kamath Fast Shipping.... - Picture 5 of 5

Transformers for Machine Learning by Uday Kamath (2022, Trade Paperback)

Bookshelf Treasures (6303)

97.3% positive feedback

Price:

$52.00

Free shipping

Estimated delivery Tue, Sep 23 - Fri, Oct 3

Returns:

30 days returns. Seller pays for return shipping.

Condition:

Brand New

NOTE: - IMAGES ARE FOR ILLUSTRATIONS ONLY.

About this product

Product Identifiers

PublisherCRC Press LLC

ISBN-100367767341

ISBN-139780367767341

eBay Product ID (ePID)4057241096

Product Key Features

SubjectGeneral

Publication Year2022

Number of Pages248 Pages

Publication NameTransformers for Machine Learning

LanguageEnglish

TypeTextbook

Subject AreaMathematics

AuthorUday Kamath

FormatTrade Paperback

Additional Product Features

LCCN2021-059529

Dewey Edition23

IllustratedYes

Dewey Decimal006.32

SynopsisTransformers are becoming a core part of many neural network architectures, employed in a wide range of applications such as NLP, Speech Recognition, Time Series, and Computer Vision. Transformers have gone through many adaptations and alterations, resulting in newer techniques and methods. Transformers for Machine Learning: A Deep Dive is the first comprehensive book on transformers. Key Features: A comprehensive reference book for detailed explanations for every algorithm and techniques related to the transformers. 60+ transformer architectures covered in a comprehensive manner. A book for understanding how to apply the transformer techniques in speech, text, time series, and computer vision. Practical tips and tricks for each architecture and how to use it in the real world. Hands-on case studies and code snippets for theory and practical real-world analysis using the tools and libraries, all ready to run in Google Colab. The theoretical explanations of the state-of-the-art transformer architectures will appeal to postgraduate students and researchers (academic and industry) as it will provide a single entry point with deep discussions of a quickly moving field. The practical hands-on case studies and code will appeal to undergraduate students, practitioners, and professionals as it allows for quick experimentation and lowers the barrier to entry into the field.

LC Classification NumberQA76.87.K354 2022