Essential Math for Data Science: Take Control of Your Data with Fundamental Calculus, Linear Algebra, Probability, and Statistics

12 reviews for Essential Math for Data Science: Take Control of Your Data with Fundamental Calculus, Linear Algebra, Probability, and Statistics

1. nesha.st

   Rated 5 out of 5

   September 26, 2023

   5.0 out of 5 stars useful

   Interests

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   Don

   Rated 5 out of 5

   August 31, 2023

   5.0 out of 5 stars Refresher for those who had extensive math in the past. Well presented for those who have not.

   Comprehensive material. Using it to get smart on the latest data science work.

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   mnowa

   Rated 5 out of 5

   August 30, 2023

   5.0 out of 5 stars Easy to ready, actually applicable to DS problems.

   Presents mathematical concepts in an approachable way that is actually applicable to DS. When they told you the math would be useful some day, this bo...More

   Presents mathematical concepts in an approachable way that is actually applicable to DS. When they told you the math would be useful some day, this book actually points out why in terms of DS problems.

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   tb

   Rated 5 out of 5

   June 4, 2023

   5.0 out of 5 stars Please fix Kindle edition

   All math equations are broken in Kindle edition. Unable to read them on kindle scribe. Returned the book. But please fix it.

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   Hemal

   Rated 5 out of 5

   May 24, 2023

   5.0 out of 5 stars Superb book

   This is one of the best books I have read, really explaining the fundamentals of math like never explained before. I am also making by teenagers read ...More

   This is one of the best books I have read, really explaining the fundamentals of math like never explained before. I am also making by teenagers read this book to clarify some concepts and develop more interest in mathematics. I highly recommend this book.

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   Chaminda Ranasinghe

   Rated 5 out of 5

   May 14, 2023

   5.0 out of 5 stars Excellent introduction to math behind the data science and ML fundamentals

   This book gives a simple and methodical background to the use of math in DS. The author makes sure that there are no gaps in the introduction of math ...More

   This book gives a simple and methodical background to the use of math in DS. The author makes sure that there are no gaps in the introduction of math knowledge of the reader when explaining the algorithms. This book makes you appreciate the theories behind DS and ML.
   
   The final chapter discloses the reality in the demand vs hype of DS skills, which is honest and valuable.
   
   Few errors in the narrations which should be fixed in the next revision.

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   Amazon Customer

   Rated 5 out of 5

   May 13, 2023

   5.0 out of 5 stars Great book

   I really enjoy the break down of the concepts and how they are applied in Data Science.

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   Cooking Texan

   Rated 5 out of 5

   April 5, 2023

   5.0 out of 5 stars Essential math revisited

   Since I retired over 20 years ago, I lost much of my familiarity with mathematical and statistical concepts. This book provides a good review of thos...More

   Since I retired over 20 years ago, I lost much of my familiarity with mathematical and statistical concepts. This book provides a good review of those concepts and made me happy to visit them again.

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   Marcelo Rezende Módolo

   Rated 4 out of 5

   February 4, 2023

   Exemplos práticos

   A leitura é fácil e os exemplos podem ser testados com facilidade.

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   Issa Ayoub

   Rated 4 out of 5

   November 4, 2022

   An excellent book to start your journey as a data scientist.

   All of the material presented in this book are important/excellent. My only comment is with regard to the grammatical mistakes which confuses the read...More

   All of the material presented in this book are important/excellent. My only comment is with regard to the grammatical mistakes which confuses the reader sometime. All in all, I highly recommend the book.

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   CookieWizard

   Rated 5 out of 5

   August 15, 2022

   5.0 out of 5 stars Great for math novices or experts alike

   I came to this with very little stats and linear algebra knowledge and no calculus. The author goes into just enough detail to be able to understand t...More

   I came to this with very little stats and linear algebra knowledge and no calculus. The author goes into just enough detail to be able to understand the math without getting overwhelmed, and the Python implementations really help break up the content and stick the math into your mind. The chapters build on each other with a final chapter on Neural Networks integrating everything you have learned previously. This chapter was a bit hard for me to completely follow and I plan to revisit it after some additional math training. This is a book I think I will go back to again and again through the next couple of years.

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   Court Miller

   Rated 5 out of 5

   July 11, 2022

   5.0 out of 5 stars Great for those who work with data - or rely on a team that works with data

   My team references this book often when explaining why they formed a conclusion from data. It's core to our business and this book outlines so compre...More

   My team references this book often when explaining why they formed a conclusion from data. It's core to our business and this book outlines so comprehensively the methods of doing it right, identifying bias, and ensuring our conclusions are accurate.
   
   This is not a how-to book. It's not even a book on math, really. This is the "why" behind working with data. It is the definitive handbook on data that every data scientist, analyst, business manager should understand before working with data.
   
   If you work with data - and just as importantly - if you rely on a team that works with data, this needs to be on your bookshelf.

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