Demystifying
Artificial
Intelligence
Simplified AI and Machine Learning
Concepts for Everyone
Prashant Kikani
www.bpbonline.com
FIRST EDITION 2021
Copyright BPB Publications, India
ISBN: 978-93-89898-705
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.
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www.bpbonline.com
Dedicated to
My family and friends, who have
provided support throughout my life
About the Author
Prashant Kikani is an experienced data scientist, who has ranks as top 1% worldwide in competitions and kernels on Kaggle, which is the worlds largest community and platform for data science and machine learning.
As part of his day-to-day work, he is trying to solve some of the hardest problems for the human kind, like language translation using state-of-the-art deep learning based NLP models and infusion of knowledge graphs in NLP models. He is one of the youngest students to achieve the Master title on the Kaggle kernel platform. Also, he has worked on other deep learning sub-fields, like computer vision via Kaggle competitions.
His interest lie in AI/ML and deep learning, and teaching others what he has learned in a simple and intuitive manner. This book is part of his interest to share his knowledge in the simplest possible manner with everyone so that they can learn about this fascinating technology called AI!
Prashants ultimate goal is to make a positive impact on millions of peoples daily lives and to always be optimistic about the future. To achieve these goals, he has started multiple initiatives. You can know more about him at
About the Reviewers
Shikhar Kwatra works as a Data and AI Architect in IBM with primary focus on Operationalizing AI models as core ML-Ops Leader. He pursued his Masters in Electrical Engineering from Columbia University. He is recognized as the Youngest Indian Master inventor with over Filed Patents and Inventions in the areas of AI/ML, IoT, Blockchain, Drones etc. He also holds the title of one of the youngest Academy of Technology members in IBM. He focuses his spare time on exploring AI-IoT technologies and leverages his technical background to work on new ideas with the aim to inspire every engineer to think from an inventive mindset.
Know more about Shikhar here: https://www.linkedin.com/in/shikharkwatra/
Darshan Patel has 1.5 years of experience in the field of data science, such as building ETL data pipelines, and developing machine learning algorithms to enable the businesses to take data-driven decisions. Darshan pursued B.Tech CSE with Specialization in Big Data Analytics from Ganpat University. He is working as a Data Science Engineer in Embibe.
Acknowledgement
I would like to thank my parents, Mr. Vinodrai and Mrs. Gulab, who have always supported me for whatever dream I wanted to pursue.
Also, I would like to thank some of my friends, who have always helped me and provided support whenever I needed it. My gratitude goes to them for being with me in my journey and allowing me to be a part of their journey as well.
This book wouldnt have come into existence if I never started exploring the machine learning and AI field in my first year of college. So, I thank all the seniors who have guided me in this field.
Finally, thanks to the publishers of this book for giving me the opportunity to write this and share my thoughts to millions of people.
Preface
In this book, we will to cover a number of topics which fall under artificial intelligence (AI).
Without requiring any kind of prerequisites, you will learn many exciting topics and concepts in the AI field in plain, simple and easy-to-understand English language.
I have made it very easy for you to understand all these mathematical based concepts by conveying them in a simple and effective manner while keeping the original concept intact.
Recently, the biggest breakthroughs in the field of AI research are being made in machine learning, especially in deep learning fields.
Why? Mainly because of the following two factors:
Availability of huge amounts of data
Comparatively cheaper powerful computation resources like GPUs (Graphics Processing Unit)
It has become easier to train machine learning systems to do certain tasks like never before.
My main focus will be on machine learning and deep learning subfields as thats what drives the artificial intelligence field nowadays.
Artificial Intelligence (AI) is a fascinating field as we are trying to copy a thing which is right there in our skull; the human brain.
Its so complex, no one to this date completely knows how it operates and takes decisions.
By the way, Mckinsy says that AI is to create $13 Trillion Value by 2030, mostly to be used in retail, followed by the travel and automotive sector.
This may be a good reason to gather some knowledge about AI!
Though the AI field is several decades old, it came to peoples attention after big tech companies started using AI and especially machine learning in their products in the last decade (i.e. 2010-2020). Before that, AI was kind of limited to research labs and universities.