热门技术看什么？这份书单告诉你！

这份书单源自网络。虽然所列图书都是免费提供的，但如果您有深入学习的打算，我还是推荐您购买纸质版书籍。作者花费大量时间整合这些资源，希望得到您的支持与喜爱！

数据科学概论

An Introduction to Data Science

Jeffrey Stanton, 2013

School of Data Handbook

School of Data, 2015

Data Jujitsu: The Art of Turning Data into Product

DJ Patil, 2012

数据科学家访谈

The Data Science Handbook

Carl Shan, Henry Wang, William Chen, & Max Song, 2015

The Data Analytics Handbook

Brian Liou, Tristan Tao, & Declan Shener, 2015

创建数据科学团队

Data Driven: Creating a Data Culture

Hilary Mason & DJ Patil, 2015

Building Data Science Teams

DJ Patil, 2011

Understanding the Chief Data Officer

Julie Steele, 2015

数据分析

The Elements of Data Analytic Style

Jeff Leek, 2015

分布式计算工具

Hadoop：权威指南

Tom White, 2011

Data-Intensive Text Processing with MapReduce

Jimmy Lin & Chris Dyer, 2010

程序语言学习

Python

像计算机科学家一样思考Python

Allen Downey, 2012

Python Programming

Wikibooks, 2015

Python编程快速上手 ——让繁琐工作自动化

Al Sweigart, 2015

“笨办法”学Python

Zed A. Shaw, 2013

R语言

R Programming for Data Science

Roger D. Peng

R Programming

Wikibooks, 2014

高级R语言编程指南

Hadley Wickham, 2014

SQL

Learn SQL The Hard Way

Zed. A. Shaw, 2010

SQL Tutorial

Tutorials Point

数据挖掘和机器学习

Introduction to Machine Learning

Amnon Shashua, 2008

Machine Learning

Abdelhamid Mellouk & Abdennacer Chebira, 450

Machine Learning – The Complete Guide

Wikipedia

社会媒体挖掘

Reza Zafarani, Mohammad Ali Abbasi, & Huan Liu, 2014

数据挖掘：实用机器学习工具与技术

Ian H. Witten & Eibe Frank, 2005

大数据：互联网大规模数据挖掘与分布式处理

Jure Leskovec, Anand Rajaraman, & Jeff Ullman, 2014

写给程序员的数据挖掘实践指南

Ron Zacharski, 2015

Data Mining with Rattle and R

Graham Williams, 2011

数据挖掘与分析：概念与算法

Mohammed J. Zaki & Wagner Meria Jr., 2014

贝叶斯方法：概率编程与贝叶斯推断

Cam Davidson-Pilon, 2015

数据挖掘技术 ——应用于市场营销、销售与客户关系管理

Michael J.A. Berry & Gordon S. Linoff, 2004

Inductive Logic Programming: Techniques and Applications

Nada Lavrac & Saso Dzeroski, 1994

Pattern Recognition and Machine Learning

Christopher M. Bishop, 2006

Machine Learning, Neural and Statistical Classification

D. Michie, D.J. Spiegelhalter, & C.C. Taylor, 1999

信息论、推理与学习算法

David J.C. MacKay, 2005

Data Mining and Business Analytics with R

Johannes Ledolter, 2013

Bayesian Reasoning and Machine Learning

David Barber, 2014

Gaussian Processes for Machine Learning

C. E. Rasmussen & C. K. I. Williams, 2006

Reinforcement Learning: An Introduction

Richard S. Sutton & Andrew G. Barto, 2012

Algorithms for Reinforcement Learning

Csaba Szepesvari , 2009

Big Data, Data Mining, and Machine Learning

Jared Dean, 2014

Modeling With Data

Ben Klemens, 2008

KB – Neural Data Mining with Python Sources

Roberto Bello, 2013

深度学习

Yoshua Bengio, Ian J. Goodfellow, & Aaron Courville, 2015

Neural Networks and Deep Learning

Michael Nielsen, 2015

Data Mining Algorithms In R

Wikibooks, 2014

Theory and Applications for Advanced Text Mining

Shigeaki Sakurai, 2012

统计和统计学习

统计思维：程序员数学之概率统计

Allen B. Downey, 2014

贝叶斯思维：统计建模的Python学习法

Allen B. Downey, 2012

统计学习导论：基于R应用

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

A First Course in Design and Analysis of Experiments

Gary W. Oehlert, 2010

数据可视化

D3 Tips and Tricks

Malcolm Maclean, 2015

数据可视化实战：使用D3设计交互式图表

Scott Murray, 2013

大数据

Disruptive Possibilities: How Big Data Changes Everything

Jeffrey Needham, 2013

Real-Time Big Data Analytics: Emerging Architecture

Mike Barlow, 2013

Big Data Now

O’Reilly Media, Inc., 2012

计算机科学

Python自然语言处理

Steven Bird, 2009

计算机视觉：算法与应用

Richard Szeliski, 2010

Concise Computer Vision

Reinhard Klette, 2010

人工智能：一种现代的方法

Stuart Russell, 1995

当看到这里的时候，您即将阅读这些经典的书籍。无论现在处于什么水平，我都希望您有自己的收获！如果有更多好书推荐，欢迎您在下方留言，谢谢！

以上为全部译文

文章原标题60+ Free Books on Big Data, Data Science, Data Mining, Machine Learning, Python, R, and more ,译者：Anchor C.,审阅：虎说八道。

文章为简译，更多内容请查看原文。