Data Science Summer Reading List 2015

Probabilistic Graphical Models: Principles and Techniques by Daphne Koller

 

Evaluating Learning Algorithms by Nathalie Japkowicz

 

Machine Learning Algorithms for Problem Solving by Siddhivinayak Kulkarni

 

Algorithms for Reinforcement Learning by Csaba Szepesvari 

 

Information Theory, Inference and Learning Algorithms by David J. C. MacKay 

 

Pattern Recognition Using Neural Networks by Carl G. Looney

 

Pattern Recognition and Machine Learning by Christopher Bishop 

 

Pattern Classification by Richard O. Duda 

Statistics Done Wrong by Alex Reinhart

Spark GraphX in Action by Michael Malak

Predictive Business Analytics by Gary Cokins

Cognitive Computing and Big Data Analytics by Judith Hurwitz

 

Probability Theory by E. T. Jaynes