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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
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Informazioni sull'autore
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.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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Numsense! Data Science for the Layman: No Math Added
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Annalyn Ng & Kenneth Soo, 2017
ISBN 10: 9811110689
ISBN 13: 9789811110689
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Numsense! Data Science for the Layman: No Math Added
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Annalyn Ng & Kenneth Soo, 2017
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ISBN 13: 9789811110689
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Numsense! Data Science for the Layman: No Math Added
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Annalyn Ng & Kenneth Soo, 2017
ISBN 10: 9811110689
ISBN 13: 9789811110689
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Numsense! Data Science for the Layman : No Math Added
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Annalyn Ng & Kenneth Soo, 2018
ISBN 10: 9811110689
ISBN 13: 9789811110689
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Numsense! Data Science for the Layman: No Math Added
Editore:
Annalyn Ng & Kenneth Soo, 2017
ISBN 10: 9811110689
ISBN 13: 9789811110689
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Paperback. Condizione: 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. Codice articolo CIN9811110689G
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Numsense! Data Science for the Layman: No Math Added
Editore:
Annalyn Ng & Kenneth Soo, 2017
ISBN 10: 9811110689
ISBN 13: 9789811110689
Antico o usato
Paperback
Da: World of Books (was SecondSale), Montgomery, IL, U.S.A.
Valutazione del venditore 5 su 5 stelle
Paperback. Condizione: 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. Codice articolo CIN9811110689A
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Numsense! Data Science for the Layman: No Math Added
Editore:
Annalyn Ng & Kenneth Soo, 2017
ISBN 10: 9811110689
ISBN 13: 9789811110689
Antico o usato
Paperback
Da: World of Books Inc, Montgomery, IL, U.S.A.
Valutazione del venditore 4 su 5 stelle
Paperback. Condizione: 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. Codice articolo CIN9811110689A
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Numsense! Data Science for the Layman: No Math Added
Editore:
Annalyn Ng & Kenneth Soo, 2017
ISBN 10: 9811110689
ISBN 13: 9789811110689
Antico o usato
Paperback
Da: World of Books Inc, Montgomery, IL, U.S.A.
Valutazione del venditore 4 su 5 stelle
Paperback. Condizione: 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. Codice articolo CIN9811110689G
Compra usato
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Numsense! Data Science for the Layman: No Math Added
Editore:
Annalyn Ng & Kenneth Soo, 2017
ISBN 10: 9811110689
ISBN 13: 9789811110689
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paperback
Da: Patrico Books, Apollo Beach, FL, U.S.A.
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paperback. Condizione: Very Good. Ships Out Tomorrow! Codice articolo 260821111
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