Books

The best books on Data Science, Big Data, Data Mining, Machine Learning, Python, R, SQL, NoSQL and more.

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4.4 (6306 Ratings)

The Visual Display of Quantitative Information

Edward R. Tufte

Theory and practice in the design of data graphics, 250 illustrations of the best (and a few of the worst) statistical graphics, with detailed analysis of how to display data for precise, effective, quick analysis.

Statistics and Statistical Learning
An Introduction to Statistical Learning with Applications in R
4.6 (1047 Ratings)

An Introduction to Statistical Learning with Applications in R

Gareth James, Daniela Witten, Trevor Hastie, & Robert Tibshirani, 2013

This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, and much more.

Learning Languages
Automate the Boring Stuff with Python: Practical Programming for Total Beginners
Languages: Python
4.4 (1013 Ratings)

Automate the Boring Stuff with Python: Practical Programming for Total Beginners

Al Sweigart, 2015

Practical programming for total beginners. In Automate the Boring Stuff with Python, you'll learn how to use Python to write programs that do in minutes what would take you hours to do by hand-no prior programming experience required.

Artificial Intelligence
Artificial Intelligence A Modern Approach, 1st Edition
4.1 (486 Ratings)

Artificial Intelligence A Modern Approach, 1st Edition

Stuart Russell, 1995

Comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Number one in its field, this textbook is ideal for one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence.

Learning Languages
Python for Informatics: Exploring Information
Languages: Python
4.3 (475 Ratings)

Python for Informatics: Exploring Information

Dr. Charles R Severance, 2013

This book is designed to introduce students to programming and computational thinking through the lens of exploring data. You can think of Python as your tool to solve problems that are far beyond the capability of a spreadsheet.

Data Visualization
Interactive Data Visualization for the Web
4.1 (433 Ratings)

Interactive Data Visualization for the Web

Scott Murray, 2013

Create and publish your own interactive data visualization projects on the Web—even if you have little or no experience with data visualization or web development. It’s easy and fun with this practical, hands-on introduction.

Computer Science Topics
Natural Language Processing with Python
Languages: Python
4.2 (405 Ratings)

Natural Language Processing with Python

Steven Bird, 2009

This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation.

Learning Languages
Python Cookbook
Languages: Python
4.4 (373 Ratings)

Python Cookbook

David Beazley & Brian K. Jones, 2013

If you need help writing programs in Python 3, or want to update older Python 2 code, this book is just the ticket. Packed with practical recipes written and tested with Python 3.3. For experienced Python developers.

Data Mining and Machine Learning
Information Theory, Inference, and Learning Algorithms
4.5 (331 Ratings)

Information Theory, Inference, and Learning Algorithms

David J.C. MacKay, 2005

"Essential reading for students of electrical engineering and computer science; also a great heads-up for mathematics students concerning the subtlety of many commonsense questions." Choice

Statistics and Statistical Learning
The Elements of Statistical Learning: Data Mining, Inference, and Prediction
4.2 (329 Ratings)

The Elements of Statistical Learning: Data Mining, Inference, and Prediction

Trevor Hastie, Robert Tibshirani, & Jerome Friedman, 2008

This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics.

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