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Learn
Python
Generative AI
Journey from autoencoders to
transformers to large language models
Zonunfeli Ralte
Indrajit Kar
www.bpbonline.com
ii
First Edition 2024
Copyright © BPB Publications, India
ISBN: 978-93-55518-972
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
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LIMITS OF LIABILITY AND DISCLAIMER OF WARRANTY
The information contained in this book is true to correct and the best of author’s and publisher’s
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
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www.bpbonline.com
Kup książkę
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Dedicated to
My beloved Parents:
R. Zohmingthanga
and
Sangthangseii
– Zonunfeli Ralte
My beloved Parents:
Avijit Kar
and
Puspa Kar
– Indrajit Kar
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About the Authors
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Zonunfeli Ralte,
a seasoned professional with a Master’s in Business Administration
and Economics, boasts 15 years of experience in Analytics, Finance, and AI.
Currently, she is the CEO and Founder of RastrAI, while also serving as a Principal
AI Consultant, developing GenAI applications for diverse industries. Zonunfeli has
an impressive academic contribution with 6 IEEE research papers including
Large
Language Models (LLM),
Deep learning and computer vision, 3 of which received
best paper awards. Her multifaceted expertise and leadership make her a notable
figure in the AI community. Additionally, she has filed 1 patent in GenAI.
Indrajit Kar,
a master’s graduate in Computational Biology from Bengaluru, also
holds a Bachelor’s in Science from the same institution with more than two decades
of experience in AI and ML. He is an experienced intrapreneur, having built AI teams
at Siemens, Accenture, IBM, and Infinite Data Systems. Presently, he is the AVP and
Global Head of AI and ML leading AI research (ZAIR) and Data Practices. Indrajit
has published 22 research papers across IEEE, Springers, Wiley Online Library, and
CRC press, covering topics like LLM, Computer Vision, NLP, and more. He has
14 patents, including Generative AI. He is a mentor for startups and a recipient of
multiple awards, including the 40 Under 40 Data Scientists award. He is also author
of 2 AI books.
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About the Reviewers
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Utkarsh Mittal
is a Machine Learning manager at Gap Inc., a global retail company.
He has more than ten years of practice experience in machine learning automation
and is a leader of big AI-based database projects. He received his Master’s in
Industrial Engineering with a Supply Chain and Operations Research major from
Oklahoma State University, USA. He is closely associated with research groups and
editorial boards of high-profile International Journals and research organizations.
He is passionate about solving complex business challenges and encouraging
innovation through upcoming technologies. He is a Senior member of the IEEE
Computer Society.
Arun Naudiyal
wears many hats, but they all share a common thread - a love for
building, learning, and driving meaningful impact. As a Senior Product Engineer at
a Big 4 Firm, his eight years of experience translate into a potent blend of expertise.
He’s the go-to for crafting and deploying Machine Learning pipelines on AWS,
wielding frameworks like Kubernetes and Sagemaker with masterful hands.
Arun’s passion extends beyond code. He’s an avid learner, constantly upskilling in
MLOps and beyond. This thirst for knowledge led him to explore the fascinating
world of Large Language Models. Under his guidance, teams have crafted projects
that revolutionized document summarization for EdTech, unearthed customer
sentiment like a treasure hunter, and even built an AI code assistant that boosts
programmer productivity.
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