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Learn Machine Learning by Doing Learn Now

Books

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

Extracting Data from NoSQL Databases
Languages: NoSQL
SQL, NoSQL, and Databases

Extracting Data from NoSQL Databases

Petter Näsholm, 2012
Machine Learning – The Complete Guide
Data Mining and Machine Learning

Machine Learning – The Complete Guide

Wikipedia
Introduction to Machine Learning
Data Mining and Machine Learning

Introduction to Machine Learning

Alex Smola & S.V.N. Vishwanathan, 2008
Cassandra Tutorial as a PDF
Languages: Cassandra
SQL, NoSQL, and Databases

Cassandra Tutorial as a PDF

Tutorials Point, 2015
R by Example
Languages: R
Learning Languages

R by Example

Ajay Shah, 2005
A Little Book of R for Time Series
Languages: R
Learning Languages

A Little Book of R for Time Series

Avril Coghlan, 2015

This is a simple introduction to time series analysis using the R statistics software.

SQL Tutorial as a PDF
Languages: SQL
SQL, NoSQL, and Databases

SQL Tutorial as a PDF

Tutorials Point

This tutorial will give you a quick start to SQL. It covers most of the topics required for a basic understanding of SQL and to get a feel of how it works.

R Programming for Data Science
Languages: R
Learning Languages

R Programming for Data Science

Roger D. Peng

This book is about the fundamentals of R programming. You will get started with the basics of the language, learn how to manipulate datasets, how to write functions, and how to debug and optimize code.

Spatial Epidemiology Notes: Applications and Vignettes in R
Languages: R
Learning Languages

Spatial Epidemiology Notes: Applications and Vignettes in R

Charles DiMaggio, 2014

My intent is to present a relatively brief, non-jargony overview of how practicing epidemiologists can apply some of the extremely powerful spatial analytic tools that are easily available to them.

Python Programming
Languages: Python
Learning Languages

Python Programming

Wikibooks, 2015

This book describes Python, an open-source general-purpose interpreted programming language available for a broad range of operating systems. This book describes primarily version 2, but does at times reference changes in version 3.

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