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Numsense! Data Science for the Layman: No Math Added by [Ng, Annalyn, Soo, Kenneth]
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Numsense! Data Science for the Layman: No Math Added Kindle Edition

4.8 out of 5 stars 42 customer reviews

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Length: 147 pages Enhanced Typesetting: Enabled Page Flip: Enabled
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Editorial Reviews

Review

"... Numsense! is a convenient graphical description of key data science algorithms, useful as an introduction for new data scientists,an overview for business people who work with analysts, or a stimulating read for anyone who wants to know what happens to their data."
-- Dr. David Stillwell
Deputy Director of The Psychometrics Centre
University of Cambridge



"... this is an excellent book to 'de-mystify' the black box of advanced statistics for business leaders who are launching studies that leverage big data."
-- Dr. Tathagata Dasgupta
Head of Data Science & Advanced Analytics
Viacom



"Numsense's examples illustrate and illuminate, but the real clarity comes from the direct writing style... This book is not just for the non-technical reader -- any programmer looking to understand data science and machine learning will quickly gain an appreciation of algorithms that other works introduce in a far less digestible form." (5/5 stars)
-- The Magpi
Leading UK tech magazine



"... Having been familiar with the work of Annalyn Ng and Kenneth Soo for some time, it comes as no surprise that the book delivers on its titular promise. This is data science for the layman, and the often-complex math--which the book describes at a high level--is intentionally not covered in detail. But don't be misled: this does not mean that the contents are in any way watered down. In fact, the information contained within is robust, with its strength being that it is abridged and concise..."
-- Matthew Mayo
Data Scientist and Editor
KDnuggets



"I like the book and highly recommend Numsense! by Ng and Soo for anyone who would like to grasp the essence of data science and machine learning, but do not want to be bugged down by mathematical and programming details... Numsense! strikes a balance between breadth and depth of data science and gives no nonsense introduction to the field."
-- Prof. Chuin-Shan Chen
Department of Civil Engineering
National Taiwan University


"... with plenty of figures and relatable examples, it succeeds in covering most important techniques in a clear, intuitive way that is perfect for novices and those seeking to improve their practice alike."
-- Barton Yadlowski
Senior Data Scientist
Pandata LLC



"Numsense's excellent visualizations of machine learning concepts helped students coming from non-technical backgrounds to grasp these abstract concepts intuitively. It presents such a succinct and precise summary for what non-technical students need to know while navigating the world of data science for the first time."
-- Ethan Chan
Lecturer for CS102 Big Data
Stanford University



"This is a great book. It is hard to explain data science without the math but this book does an amazing job. It balances both the simplicity and the depth."
-- Ajit Jaokar
Data Science for Internet of Things
University of Oxford

From the Author

Numsense! is dedicated to you by two data science enthusiasts, Annalyn Ng (University of Cambridge) and Kenneth Soo (Stanford University).

We noticed that while data science is increasingly used to improve workplace decisions, many know little about the field. Hence, we compiled these tutorials into a book so that more people can learn--be it an aspiring student, enterprising business professional, or anyone with a curious mind.

Product details

  • File Size: 13978 KB
  • Print Length: 147 pages
  • Publication Date: February 3, 2017
  • Sold by: Amazon Digital Services LLC
  • Language: English
  • ASIN: B01N29ZEM6
  • Text-to-Speech: Enabled
  • X-Ray:
  • Word Wise: Not Enabled
  • Lending: Enabled
  • Screen Reader: Supported
  • Enhanced Typesetting: Enabled
  • Amazon Best Sellers Rank: #6,407 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
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on November 9, 2017
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on October 6, 2017
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on November 10, 2017
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on May 9, 2017
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