Numsense! Data Science for the Layman: No Math Added
Language: English
Published by Annalyn Ng & Kenneth Soo, 2017
- Softcover
- Used
Seller: World of Books (was SecondSale), Montgomery, IL, U.S.A.World of Books (was SecondSale)
AbeBooks seller since December 20, 2007
Condition: Used - Good
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Add to basketItem description from seller
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
- Title
- Numsense! Data Science for the Layman: No Math Added
- Author
- Kenneth Soo
- Publisher
- Annalyn Ng & Kenneth Soo
- Publication year
- 2017
- Condition
- Good
- Binding
- Paperback
- Language
- English
- ISBN 10
- 9811110689
- ISBN 13
- 9789811110689
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 graduated from the University of Michigan (Ann Arbor), where she also was an undergraduate statistics tutor. She then completed her MPhil degree with the University of Cambridge Psychometrics Centre, where she mined social media data for targeted advertising and programmed cognitive tests for job recruitment. Disney Research later roped her into their behavioral sciences team, where she examined psychological profiles of consumers.
Kenneth Soo is due to complete his MS degree in Statistics at Stanford University by mid-2017. 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, where he was also a research assistant with the Operational Research & Management Sciences Group, working on bi-objective robust optimization with applications in networks subject to random failures.
"About the title" may belong to another edition of this title.
World of Books (was SecondSale)
Montgomery, IL, U.S.A.
AbeBooks seller since December 20, 2007
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