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Joel Grus

Data Science from Scratch: First Principles with Python Paperback – 30 April 2019

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To really learn data science, you should not only master the tools&;data science libraries, frameworks, modules, and toolkits&;but also understand the ideas and principles underlying them. Updated for Python 3.6, this second edition of Data Science from Scratch shows you how these tools and algorithms work by implementing them from scratch.

If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with the hacking skills you need to get started as a data scientist. Packed with new material on deep learning, statistics, and natural language processing, this updated book shows you how to find the gems in today&;s messy glut of data.

Get a crash course in Python
Learn the basics of linear algebra, statistics, and probability&;and how and when they&;re used in data science
Collect, explore, clean, munge, and manipulate data
Dive into the fundamentals of machine learning
Implement models such as k-nearest neighbors, Naïve Bayes, linear and logistic regression, decision trees, neural networks, and clustering
Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

ISBN-10

1492041130
ISBN-13

978-1492041139
Edition

2
Publisher

O'Reilly Media, Inc, USA
Publication date

30 April 2019
Language

English
Dimensions

17.53 x 2.29 x 23.11 cm
Print length

500 pages
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From the Publisher


	Data Science for Business	Data Science from Scratch	Doing Data Science	R for Data Science	Data Science at the Command Line	Python Data Science Handbook
	What You Need to Know about Data Mining and Data-Analytic Thinking	First Principles with Python	Straight Talk from the Frontline	Visualize, Model, Transform, Tidy, and Import Data	Facing the Future with Time-Tested Tools	Tools and Techniques for Developers

Product description

About the Author

Joel Grus is a software engineer at Google. Before that he worked as a data scientist at multiple startups. He lives in Seattle, where he regularly attends data science happy hours.

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Product details

Publisher ‏ : ‎ O'Reilly Media, Inc, USA; 2 edition (30 April 2019)
Language ‏ : ‎ English
Paperback ‏ : ‎ 500 pages
ISBN-10 ‏ : ‎ 1492041130
ISBN-13 ‏ : ‎ 978-1492041139
Dimensions ‏ : ‎ 17.53 x 2.29 x 23.11 cm

Best Sellers Rank: 20,116 in Books (See Top 100 in Books)
- 6 in Computer Algorithms Textbooks
- 13 in Database Storage & Design Textbooks
- 39 in Statistics (Books)

Customer Reviews:
480 ratings

About the author

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Joel Grus

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Joel Grus is Principal Engineer at Capital Group, where he leads a small team that designs and implements machine learning and data products. Before that he was a software engineer at the Allen Institute for AI and Google, and a data scientist at a variety of startups.

He's the author of the the beloved "Data Science from Scratch", the quirky "Ten Essays on Fizz Buzz", and the polarizing JupyterCon talk "I Don't Like Notebooks".

He lives in Seattle, where he regularly attends data science happy hours. He blogs infrequently at joelgrus.com.

Customer reviews

5 star		70%
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3 star		7%
2 star		3%
1 star		4%

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Very basic, low quality paper and print

Reviewed in Australia on 16 September 2020

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It is supposed to be about fundamentals, and nothing really advance, so I cannot really say I expected more from it in terms of what this book covers, but the quality of the book is shockingly bad. Paper and print qualities are unbelievably bad. Grayscale figure, low DPI, makes hard to read it.

One person found this helpful

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Java Exam

Fantastic !

Reviewed in Australia on 23 July 2020

Verified Purchase

I enjoyed this book so much I read it three times. Get Py Charm community edition from Intellij to make your coding life easier. Looking forward to the maths for machine learning from O'reilly later in the year.

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Top reviews from other countries

Martin

The Paperback is black & white and very poor quality

Reviewed in the United Kingdom on 25 August 2020

Verified Purchase

The paperback unfortunately was not printed in colour, only a low resolution black & white, which I was very disappointed with for an O'Reilly book. Colour conveys important information in a book like this.
Without colour coding in the graphs, and with syntax highlighting missing for the code segments, it makes the book very difficult to read.

I'm sure the book itself is great, and I'm looking forward to reading the ePub instead.

16 people found this helpful

El Chubinebrae

Good book, bit pricey though.

Reviewed in the United Kingdom on 15 October 2020

Verified Purchase

This is a good book. It's been updated for Python 3 so you won't miss out on any of the new features.

It's definitely not for complete beginners. If you have a foundational knowledge of python then you'll understand some of the concepts outlined. It's also not a tutorial book either, the best way to use this book is to find a part of it and apply it to a data set.

5 people found this helpful

MR S S DADWAL

Misreported

Reviewed in the United Kingdom on 25 January 2021

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This book is actually 380 pages long, not 500 as reported

7 people found this helpful

Velvetytoast

Very good ground up approach to the subject

Reviewed in the United Kingdom on 25 January 2020

Verified Purchase

It’s definitely from the ground up - I found it useful to revisit the maths as well as seeing the code - well with the price of the book

3 people found this helpful

Ed

Very good book

Reviewed in the United Kingdom on 2 January 2020

Verified Purchase

Very good book, I highly recommend it for early stage Data scientists

4 people found this helpful

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