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Tamoghna Ghosh - Practical Mathematics for AI and Deep Learning: A Concise yet In-Depth Guide on Fundamentals of Computer Vision, NLP, Complex Deep Neural Networks and Machine Learning

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Tamoghna Ghosh Practical Mathematics for AI and Deep Learning: A Concise yet In-Depth Guide on Fundamentals of Computer Vision, NLP, Complex Deep Neural Networks and Machine Learning
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Mathematical Codebook to Navigate Through the Fast-changing AI LandscapeKey Features Access to industry-recognized AI methodology and deep learning mathematics with simple-to-understand examples. Encompasses MDP Modeling, the Bellman Equation, Auto-regressive Models, BERT, and Transformers. Detailed, line-by-line diagrams of algorithms, and the mathematical computations they perform.DescriptionTo construct a system that may be referred to as having Artificial Intelligence, it is important to develop the capacity to design algorithms capable of performing data-based automated decision-making in conditions of uncertainty. Now, to accomplish this goal, one needs to have an in-depth understanding of the more sophisticated components of linear algebra, vector calculus, probability, and statistics. This book walks you through every mathematical algorithm, as well as its architecture, its operation, and its design so that you can understand how any artificial intelligence system operates.This book will teach you the common terminologies used in artificial intelligence such as models, data, parameters of models, and dependent and independent variables. The Bayesian linear regression, the Gaussian mixture model, the stochastic gradient descent, and the backpropagation algorithms are explored with implementation beginning from scratch. The vast majority of the sophisticated mathematics required for complicated AI computations such as autoregressive models, cycle GANs, and CNN optimization are explained and compared.You will acquire knowledge that extends beyond mathematics while reading this book. Specifically, you will become familiar with numerous AI training methods, various NLP tasks, and the process of reducing the dimensionality of data.

Tamoghna Ghosh: author's other books


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Tamoghna Ghosh - Practical Mathematics for AI and Deep Learning: A Concise yet In-Depth Guide on Fundamentals of Computer Vision, NLP, Complex Deep Neural Networks and Machine Learning
Practical Mathematics for AI and Deep Learning: A Concise yet In-Depth Guide on Fundamentals of Computer Vision, NLP, Complex Deep Neural Networks and Machine Learning
Tamoghna Ghosh
Practical Mathematics for AI and Deep Learning: A Concise yet In-Depth Guide on Fundamentals of Computer Vision, NLP, Complex Deep Neural Networks and Machine Learning
Tamoghna Ghosh - Hands-On Transfer Learning with Python
Hands-On Transfer Learning with Python
Tamoghna Ghosh
Hands-On Transfer Learning with Python

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Table of Contents
Guide

Practical Mathematics for AI and Deep Learning - photo 1

Practical
Mathematics for AI
and Deep Learning

A Concise yet In-Depth Guide on Fundamentals of Computer Vision NLP Complex - photo 2

A Concise yet In-Depth Guide on Fundamentals
of Computer Vision, NLP, Complex Deep Neural
Networks and Machine Learning

Practical Mathematics for AI and Deep Learning A Concise yet In-Depth Guide on Fundamentals of Computer Vision NLP Complex Deep Neural Networks and Machine Learning - image 3

Tamoghna Ghosh
Shravan Kumar Belagal Math
Practical Mathematics for AI and Deep Learning A Concise yet In-Depth Guide on Fundamentals of Computer Vision NLP Complex Deep Neural Networks and Machine Learning - image 4

www.bpbonline.com

FIRST EDITION 2023

Copyright BPB Publications, India

ISBN: 978-93-5551-194-2

All Rights Reserved. No part of this publication may be reproduced, distributed or transmitted in any form or by any means or stored in a database or retrieval system, without the prior written permission of the publisher with the exception to the program listings which may be entered, stored and executed in a computer system, but they can not be reproduced by the means of publication, photocopy, recording, or by any electronic and mechanical means.

LIMITS OF LIABILITY AND DISCLAIMER OF WARRANTY

The information contained in this book is true to correct and the best of authors and publishers knowledge. The author has made every effort to ensure the accuracy of these publications, but publisher cannot be held responsible for any loss or damage arising from any information in this book.

All trademarks referred to in the book are acknowledged as properties of their respective owners but BPB Publications cannot guarantee the accuracy of this information.

wwwbpbonlinecom Dedicated to From Tamoghna My grandfather late - photo 5

www.bpbonline.com

Dedicated to

From Tamoghna

My grandfather, late Mr. Dukari Roychoudhury who introduced me to a great Mathematics teacher and always guided me with his wise words.

My beloved grandmother, late Mrs. Renuka Roychoudhury.

From Shravan

Parents Basavaraj & Sulakshana, who supported me in all phases of life and continue to do so.

Brother Chethan, whose thinking always is in sync with mine, rarely we disagree on any topic.

Charming spouse Sudha, who has always encouraged me to achieve greater heights.

Adorable kids Anvika & Anirudh, whose presence keeps us cheerful.

About the Authors

Tamoghnais an AI Software Solutions Engineer in Client Computing Group at Intel and has 15 years of work experience. He has a masters in computer science from Indian Statistical Institute and a masters in mathematics form Calcutta University. He has 4 US patents, 3 IEEE papers and has also authored book on Transfer learning.

Shravanis currently an AI Engineer at Intels Client Computing Group with 11 years of working experience. He had Master of Engineering degree from Indian Institute of Science, Computer Science and Automation department. He has been granted with 4 US patents. His interest lies in application of AI algorithms to solve real world problems.

About the Reviewer

Koushik Bhattacharyyais an accomplished Software Professional, who after completing M.Sc Pure Mathematics from Burdwan University and M.Tech in Computer Science (Gold Medalist) from Indian Statistical Institute, Kolkata, worked for technology giants like NVIDIA, AMD, Toshiba and Intel. He has more than 18 years of experience in software development with Architectures and Lead roles in diverse domains and technologies, including Medical Image Processing, Computer Vision, Machine Learning, Deep Learning, GPGPU and more. Koushik has also authored a book viz. OpenCL Programming by Example.

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