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Analytics in a Big Data World: The Essential Guide to Data Science and its Applications, by Bart Baesens.
Visualize This: The FlowingData Guide to Design, Visualization, and Statistics, by Nathan Yau.
Bayesian Reasoning and Machine Learning, by David Barber.
Bayesian Data Analysis, Third Edition, by Andrew Gelman, et al.
Fast Data Processing with Spark, by Holden Karau.
Social Physics: How Good Ideas Spread, by Alex Pentland.
The Naked Future: What Happens in a World That Anticipates Your Every Move?, by Patrick Tucker.
Think Like a Freak, by Steven Levitt & Stephen Dubner.
Practical Data Science with R, by Nina Zumel & John Mount.
Developing Analytic Talent: Becoming a Data Scientist, by Vincent Granville.
The Signal and the Noise: Why So Many Predictions Fail — but Some Don't, by Nate Silver.
Data Smart: Using Data Science to Transform Information into Insight, by John W. Foreman.
Agile Data Science: Building Data Analytics Applications with Hadoop, by Russell Jurney.
Machine Learning for Hackers, by Drew Conway & John Myles White.
Machine Learning with R, by Brett Lantz.
Modeling Techniques in Predictive Analytics: Business Problems and Solutions with R, by Thomas Miller.
Outlier Analysis, by Charu C. Aggarwal.
Anomaly Detection Technique for Sequential Data, by Muriel Pellissier.