摘要： 這是一份關於數據科學、商業分析、大數據、機器學習、演算法、數據科學工具和相關程序語言的福利書單。又騙你買書？不，我們還有電子書！心動不如行動，趕快進來看看吧！

這份書單源自網路。雖然所列圖書都是免費提供的，但如果您有深入學習的打算，我還是推薦您購買紙質版書籍。作者花費大量時間整合這些資源，希望得到您的支持與喜愛！

數據科學概論

• 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

數據科學家訪談

• The Data Science Handbook

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

• The Data Analytics Handbook

Brian Liou, Tristan Tao, & Declan Shener, 2015

創建數據科學團隊

• 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

數據分析

• The Elements of Data Analytic Style

Jeff Leek, 2015

分散式計算工具

• Hadoop：權威指南

Tom White, 2011

• Data-Intensive Text Processing with MapReduce

Jimmy Lin & Chris Dyer, 2010

程序語言學習

Python

• 像計算機科學家一樣思考Python

Allen Downey, 2012

• Python Programming

Wikibooks, 2015

• Python編程快速上手 ——讓繁瑣工作自動化

Al Sweigart, 2015

• 「笨辦法」學Python

Zed A. Shaw, 2013

R語言

• R Programming for Data Science

Roger D. Peng

• R Programming

Wikibooks, 2014

• 高級R語言編程指南

Hadley Wickham, 2014

SQL

• Learn SQL The Hard Way

Zed. A. Shaw, 2010

• SQL Tutorial

Tutorials Point

數據挖掘和機器學習

• Introduction to Machine Learning

Amnon Shashua, 2008

• Machine Learning

Abdelhamid Mellouk & Abdennacer Chebira, 450

• Machine Learning – The Complete Guide

Wikipedia

• 社會媒體挖掘

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

• 數據挖掘：實用機器學習工具與技術

Ian H. Witten & Eibe Frank, 2005

• 大數據：互聯網大規模數據挖掘與分散式處理

Jure Leskovec, Anand Rajaraman, & Jeff Ullman, 2014

• 寫給程序員的數據挖掘實踐指南

Ron Zacharski, 2015

• Data Mining with Rattle and R

Graham Williams, 2011

• 數據挖掘與分析：概念與演算法

Mohammed J. Zaki & Wagner Meria Jr., 2014

• 貝葉斯方法：概率編程與貝葉斯推斷

Cam Davidson-Pilon, 2015

• 數據挖掘技術 ——應用於市場營銷、銷售與客戶關係管理

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

• 資訊理論、推理與學習演算法

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

• 深度學習

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

統計和統計學習

• 統計思維：程序員數學之概率統計

Allen B. Downey, 2014

• 貝葉斯思維：統計建模的Python學習法

Allen B. Downey, 2012

• 統計學習導論：基於R應用

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

• A First Course in Design and Analysis of Experiments

Gary W. Oehlert, 2010

數據可視化

• D3 Tips and Tricks

Malcolm Maclean, 2015

• 數據可視化實戰：使用D3設計互動式圖表

Scott Murray, 2013

大數據

• 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

計算機科學

• Python自然語言處理

Steven Bird, 2009

• 計算機視覺：演算法與應用

Richard Szeliski, 2010

• Concise Computer Vision

Reinhard Klette, 2010

• 人工智慧：一種現代的方法

Stuart Russell, 1995

當看到這裡的時候，您即將閱讀這些經典的書籍。無論現在處於什麼水平，我都希望您有自己的收穫！如果有更多好書推薦，歡迎您在下方留言，謝謝！

以上為全部譯文

文章原標題60+ Free Books on Big Data, Data Science, Data Mining, Machine Learning, Python, R, and more ,譯者：Anchor C.,審閱：虎說八道。

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