Data Scientist Pocket Guide: Over 600 Concepts, Terminologies, and Processes of Machine Learning and Deep Learning Assembled Together (English Edition)

866 Pages·2021·9.088 MB·English

by  Mohamed Sabri

Data Scientist
Pocket Guide
Over 600 Concepts, Terminologies, and
Processes of Machine Learning and
Deep Learning Assembled Together
Mohamed Sabri
www.bpbonline.com
FIRST EDITION 2021
Copyright © BPB Publications, India
ISBN: 978-93-90684-97-7
All Rights Reserved. No part of this publication may be
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computer system, but they can not be reproduced by the means
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mechanical means.
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.
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Dedicated to
My father and our Sundays…
About the Author
Mohamed the author of this book, completed his graduation in
Mathematics and Economics from the University of Ottawa. He is
a Managing Partner and Consultant in the field of Data Science
and MLOps, and is working with the North American
organizations in the Banking, Retail, and Gaming sector. With an
irrefutable passion for Data Science, he is driven to do more for
the domain by being involved in a range of innovative AI projects
that help him deliver end-to-end solutions in the field of AI.
He drives his professional journey with his excellent
communication skills and his expertise in Tech popularisation for
complex projects. Building upon his commitment towards ensuring
work and team cohesiveness, he has successfully executed several
AI projects.
In his book, “Data Scientist Pocket Guide”, he has interestingly
poured his secrets of becoming a benevolent data scientist.
His secret passion for connecting and networking with people and
professionals is channelled through this book, that attempts to
connect and reach several data scientists and make their everyday
job enriching and easier.
About the Reviewer
Prateek Gupta is a Data Enthusiast and loves data-driven
technologies. Prateek has done his B.Tech in Computer Science &
Engineering and currently working as a Data Scientist in an IT
company. Prateek has a total of 10 years of experience in the
software industry, and currently, he is working in the Computer
Vision area. Prateek is also author of the book “Practical Data
Science with Jupyter” 2 nd Edition published by the BPB
Publications.
Acknowledgements
The completion of this book could not have been possible without
the support of BPB Publications. I would like to thank all the
team members of BPB Publications; despite the COVID crisis, they
extended their full support with access to all the resources that
were critical in completing this book. I would like to thank my
family for their support and encouragement while writing this
book, with a special mention to my parents for being an
incredible source of inspiration in my life. A huge thanks to my
father for teaching me how to be patient and resilient in life.
Lastly, I would like to underline the importance of patience in
writing a book or facing any challenge in life.
Preface
At the beginning of my career as a data scientist, I use to go on
search engines and use various sources to find explanations about
a concept in data science. This was time consuming and the
answers to my questions where not always reliable. It is hard for
any data scientist to find quickly all the answers to his questions
and sometimes answers vary from a source to another. Also,
some concepts are hard to understand so you have to find a
source that explains clearly what a concept means. This book is a
first of a kind dictionary or glossary that regroups the most
popular terms in data science. It helps data scientist from
beginners to senior to look for definitions very quickly and have
reliable answers to their questions. Usually books in data science
focuses on coding and on practical use cases, whereas this book
goal is to explain concepts and give a better idea to data scientist
about what the words means. It’s good to be able to code in
data science and build machine learning models but if the data
scientist doesn’t understand the logic and the mechanism behind
each concept it is hard for him to provide good results and
explain its work. I hope you will keep this book as your Bible for
data science and use it each time you have doubt about a
concept’s meaning. Have fun!
This book is separated into two sections. The first section is
composed of 26 chapters, each chapter correspond to a letter in
the alphabet and a set of definitions in each chapter. The second
section is an FAQ or frequently asked questions and it contains
all the questions that a data scientist might have when it comes