Wuyi Free Data Science Books
A great collection of free data science books covering a wide range of topics from data science, business Analytics, data Mining and Big data to machine learning, algorithms and Data Science Tools.
Data Science Overviews
- An Introduction to Data science (Jeffrey Stanton, 2013)
- School of Data Handbook (2015)
- Data jujitsu:the Art of Turning data into Product (DJ Patil, 2012)
- Art of Data Science (Roger D. Peng & Elizabeth Matsui, 2015)
Data Scientists interviews
- The Data Science Handbook (Carl Shan, Henry Wang, William Chen, & Max Song, 2015)
- The Data Analytics Handbook (Brian Liou, Tristan Tao, & Declan Shener, 2015)
How to Build Data science Teams
- Data driven:creating a data Culture (Hilary Mason & DJ Patil, 2015)
- Building Data Science Teams (DJ Patil, 2011)
- Understanding the Chief Data O€fficer (Julie Steele, 2015)
Data Analysis
- The Elements of Data Analytic Style (Jeff Leek, 2015)
Distributed Computing Tools
- Hadoop:the Definitive Guide (Tom white, 2011)
- Data-intensive Text processing with MapReduce (Jimmy Lin & Chris Dyer, 2010)
Data Mining and machine learning
- Introduction to Machine learning (Amnon Shashua, 2008)
- Machine learning (Abdelhamid Mellouk & Abdennacer Chebira)
- Machine learning–the Complete Guide (Wikipedia)
- Social Media Mining an Introduction (Reza Zafarani, Mohammad Ali Abbasi, & Huan Liu, 2014)
- Data mining:practical Machine learning Tools and techniques (Ian H. Witten & Eibe Frank, 2005)
- Mining of Massive Datasets (Jure Leskovec, Anand Rajaraman, & Jeff Ullman, 2014)
- A Programmer ' s Guide to Data Mining (Ron Zacharski, 2015)
- Data Mining with Rattle and R (Graham Williams, 2011)
- Data Mining and Analysis:fundamental Concepts and Algorithms (Mohammed J. Zaki & Wagner Meria Jr., 2014)
- Mining the social web:data Mining Facebook, Twitter, LinkedIn, Google +, GitHub, and more (Matthew A. Russell, 2014)
- Probabilistic Programming & Bayesian Methods for Hackers (Cam Davidson-pilon, 2015)
- Data Mining Techniques for Marketing, Sales, and Customer relationship Management (Michael j.a. Berry & Gordon S. Lino FF, 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)
- Information theory, inference, and Learning algorithms (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. 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)
- Deep Learning (Yoshua Bengio, Ian J. Goodfellow, & Aaron Courville, 2015)
- Neural Networks and deep learning (Michael Nielsen, 2015)
- Data Mining Algorithms in R (Wikibooks, 2014)
- Data Mining and Analysis:fundamental Concepts and Algorithms (Mohammed J. Zaki & Wagner Meira Jr., 2014)
- Theory and applications for Advanced Text Mining (Shigeaki Sakurai, 2012)
Statistics and statistical learning
- Think stats:exploratory Data Analysis in Python (Allen B. Downey, 2014)
- Think Bayes:bayesian Statistics Made Simple (Allen B. Downey, 2012)
- The Elements of statistical learning:data Mining, inference, and prediction (Trevor Hastie, Robert Tibshirani, & Jero Me Friedman, 2008)
- An Introduction to statistical learning with applications in R (Gareth James, Daniela Witten, Trevor Hastie, & Robert Tibshirani, 2013)
- A first Course in Design and analysis of Experiments (Gary W. Oehlert, 2010)
Data Visualization
- D3 Tips and Tricks (Malcolm Maclean, 2015)
- Interactive Data Visualization for the Web (Scott Murray, 2013)
Big Data
- Disruptive possibilities:how Big Data changes Everything (Jeffrey Needham, 2013)
- Real-time Big Data analytics:emerging Architecture (Mike Barlow, 2013)
- Big Data now:2012 Edition (O ' Reilly Media, Inc., 2012)
Wuyi Free Data Science Books
