Items related to Numsense! Data Science for the Layman: No Math Added
Synopsis
Reference text in top universities like Stanford and Cambridge
Sold in over 85 countries, translated into more than 5 languages
Want to get started on data science? Our promise: no math added. This book has been written in layman’s terms as a gentle introduction to data science and its algorithms. Each algorithm has its own dedicated chapter that explains how it works, and shows an example of a real-world application. To help you grasp key concepts, we stick to intuitive explanations and visuals.
Popular concepts covered include:
- A/B Testing
- Anomaly Detection
- Association Rules
- Clustering
- Decision Trees and Random Forests
- Regression Analysis
- Social Network Analysis
- Neural Networks
- Intuitive explanations and visuals
- Real-world applications to illustrate each algorithm
- Point summaries at the end of each chapter
- Reference sheets comparing the pros and cons of algorithms
- Glossary list of commonly-used terms
"synopsis" may belong to another edition of this title.
About the Author
Annalyn Ng is an AI/ML specialist at Google Cloud. Her data science career spans across commercial and public sectors; she has held roles in Amazon, Disney Research, as well as in the Singapore government, specifically in the manpower and military ministries. Annalyn earned her bachelor's degree from the University of Michigan (Ann Arbor), where she also volunteered as an undergraduate statistics tutor, and subsequently completed her MPhil degree at the University of Cambridge.
Kenneth Soo has 7 years of experience applying data science to public policy for the Singapore government, and he currently leads a team managing bilateral relations with European partners. During the COVID-19 pandemic, he drove nationwide digitalization initiatives for Singapore's Smart Nation and Digital Government Office, including the implementation of contact tracing systems. He completed his MS degree in Statistics at Stanford University, and he was the top student for all three years of his undergraduate class in Mathematics, Operational Research, Statistics and Economics (MORSE) at the University of Warwick.
"About this title" may belong to another edition of this title.
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Numsense! Data Science for the Layman: No Math Added
Published by
Annalyn Ng & Kenneth Soo, 2017
ISBN 10: 9811110689
ISBN 13: 9789811110689
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Numsense! Data Science for the Layman: No Math Added
Published by
Annalyn Ng & Kenneth Soo, 2017
ISBN 10: 9811110689
ISBN 13: 9789811110689
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Numsense! Data Science for the Layman: No Math Added
Published by
Annalyn Ng & Kenneth Soo, 2017
ISBN 10: 9811110689
ISBN 13: 9789811110689
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Numsense! Data Science for the Layman: No Math Added
Published by
Annalyn Ng & Kenneth Soo, 2017
ISBN 10: 9811110689
ISBN 13: 9789811110689
Used
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Numsense! Data Science for the Layman : No Math Added
Published by
Annalyn Ng & Kenneth Soo, 2018
ISBN 10: 9811110689
ISBN 13: 9789811110689
Used
Softcover
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Numsense! Data Science for the Layman: No Math Added
Published by
Annalyn Ng & Kenneth Soo, 2017
ISBN 10: 9811110689
ISBN 13: 9789811110689
Used
Paperback
Seller: World of Books (was SecondSale), Montgomery, IL, U.S.A.
Seller rating 5 out of 5 stars
Paperback. Condition: Good. Used in Stanford's CS102 Big Data (Spring 2017) course. Want to get started on data science? Our promise: no math added. This book has been written in layman's terms as a gentle introduction to data science and its algorithms. Each algorithm has its own dedicated chapter that explains how it works, and shows an example of a real-world application. To help you grasp key concepts, we stick to intuitive explanations, as well as lots of visuals, all of which are colorblind-friendly. Popular concepts covered include: A/B Testing Anomaly Detection Association Rules Clustering Decision Trees and Random Forests Regression Analysis Social Network Analysis Neural Networks Features: Intuitive explanations and visuals Real-world applications to illustrate each algorithm Point summaries at the end of each chapter Reference sheets comparing the pros and cons of algorithms Glossary list of commonly-used terms With this book, we hope to give you a practical understanding of data science, so that you, too, can leverage its strengths in making better decisions. Seller Inventory # CIN9811110689G
Stock Image
Numsense! Data Science for the Layman: No Math Added
Published by
Annalyn Ng & Kenneth Soo, 2017
ISBN 10: 9811110689
ISBN 13: 9789811110689
Used
Paperback
Seller: World of Books (was SecondSale), Montgomery, IL, U.S.A.
Seller rating 5 out of 5 stars
Paperback. Condition: Fair. Used in Stanford's CS102 Big Data (Spring 2017) course. Want to get started on data science? Our promise: no math added. This book has been written in layman's terms as a gentle introduction to data science and its algorithms. Each algorithm has its own dedicated chapter that explains how it works, and shows an example of a real-world application. To help you grasp key concepts, we stick to intuitive explanations, as well as lots of visuals, all of which are colorblind-friendly. Popular concepts covered include: A/B Testing Anomaly Detection Association Rules Clustering Decision Trees and Random Forests Regression Analysis Social Network Analysis Neural Networks Features: Intuitive explanations and visuals Real-world applications to illustrate each algorithm Point summaries at the end of each chapter Reference sheets comparing the pros and cons of algorithms Glossary list of commonly-used terms With this book, we hope to give you a practical understanding of data science, so that you, too, can leverage its strengths in making better decisions. Seller Inventory # CIN9811110689A
Stock Image
Numsense! Data Science for the Layman: No Math Added
Published by
Annalyn Ng & Kenneth Soo, 2017
ISBN 10: 9811110689
ISBN 13: 9789811110689
Used
Paperback
Seller: World of Books Inc, Montgomery, IL, U.S.A.
Seller rating 4 out of 5 stars
Paperback. Condition: Fair. Used in Stanford's CS102 Big Data (Spring 2017) course. Want to get started on data science? Our promise: no math added. This book has been written in layman's terms as a gentle introduction to data science and its algorithms. Each algorithm has its own dedicated chapter that explains how it works, and shows an example of a real-world application. To help you grasp key concepts, we stick to intuitive explanations, as well as lots of visuals, all of which are colorblind-friendly. Popular concepts covered include: A/B Testing Anomaly Detection Association Rules Clustering Decision Trees and Random Forests Regression Analysis Social Network Analysis Neural Networks Features: Intuitive explanations and visuals Real-world applications to illustrate each algorithm Point summaries at the end of each chapter Reference sheets comparing the pros and cons of algorithms Glossary list of commonly-used terms With this book, we hope to give you a practical understanding of data science, so that you, too, can leverage its strengths in making better decisions. Seller Inventory # CIN9811110689A
Stock Image
Numsense! Data Science for the Layman: No Math Added
Published by
Annalyn Ng & Kenneth Soo, 2017
ISBN 10: 9811110689
ISBN 13: 9789811110689
Used
Paperback
Seller: World of Books Inc, Montgomery, IL, U.S.A.
Seller rating 4 out of 5 stars
Paperback. Condition: Good. Used in Stanford's CS102 Big Data (Spring 2017) course. Want to get started on data science? Our promise: no math added. This book has been written in layman's terms as a gentle introduction to data science and its algorithms. Each algorithm has its own dedicated chapter that explains how it works, and shows an example of a real-world application. To help you grasp key concepts, we stick to intuitive explanations, as well as lots of visuals, all of which are colorblind-friendly. Popular concepts covered include: A/B Testing Anomaly Detection Association Rules Clustering Decision Trees and Random Forests Regression Analysis Social Network Analysis Neural Networks Features: Intuitive explanations and visuals Real-world applications to illustrate each algorithm Point summaries at the end of each chapter Reference sheets comparing the pros and cons of algorithms Glossary list of commonly-used terms With this book, we hope to give you a practical understanding of data science, so that you, too, can leverage its strengths in making better decisions. Seller Inventory # CIN9811110689G
Stock Image
Numsense! Data Science for the Layman: No Math Added
Published by
Annalyn Ng & Kenneth Soo, 2017
ISBN 10: 9811110689
ISBN 13: 9789811110689
Used
paperback
Seller: Patrico Books, Apollo Beach, FL, U.S.A.
Seller rating 5 out of 5 stars
paperback. Condition: Very Good. Ships Out Tomorrow! Seller Inventory # 260821111