1. Data Mining: Concepts and Techniques, Jiawei Han and Micheline Kamber
   About data mining and data warehousing
2. Mining of Massive Datasets, Jure Leskovec, Anand Rajaraman, Jeff Ullman
   The focus of this book is provide the necessary tools and knowledge to manage, manipulate and consume large chunks of information into databases.
3. The Elements of Statistical Learning, Trevor Hastie, Robert Tibshirani, Jerome Friedman
   This is a conceptual book in terms of data mining and prediction with a statistical point of view. Covers many machine learning subjects too.
4. An Introduction to Statistical Learning: with Applications in R, Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani
   Overview of statistical learning based on large datasets of information. The exploratory techniques of the data are discussed using the R programming language.
5. Data Science for Business, Foster Provost, Tom Fawcett
   An introduction to data sciences principles and theory, explaining the necessary analytical thinking to approach these kind of problems. It discusses various data mining techniques to explore information.
6. Modeling With Data
   This book focus some processes to solve analytical problems applied to data. In particular explains you the theory to create tools for exploring big datasets of information.
7. Big Data, Data Mining, and Machine Learning: Value Creation for Bus…
   On this resource the reality of big data is explored, and its benefits, from the marketing point of view. It also explains how to storage these kind of data and algorithms to process it, based on data mining and machine learning.
8. Data Mining: Practical Machine Learning Tools and Techniques
   Full of real world situations where machine learning tools are applied, this is a practical book which provides you the knowledge and hability to master the whole process of machine learning.
9. Machine Learning – Wikipedia Guide
   A great resource provided by Wikipedia assembling a lot of machine learning in a simple, yet very useful and complete guide.
10. Data Mining and Analysis: Fundamental Concepts and Algorithms
    A great cover of the data mimning exploratory algorithms and machine learning processes. These explanations are complemented by some statistical analysis.
11. Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Goo…
    The exploration of social web data is explained on this book. Data capture from the social media apps, it’s manipulation and the final visualization tools are the focus of this resource.
12. Probabilistic Programming & Bayesian Methods for Hackers
    A book about bayesian networks that provide capabilities to solve very complex problems. Also discusses programming implementations on the Python language.
13. Data Mining Techniques: For Marketing, Sales, and Customer Relation…
    A data mining book oriented specifically to marketing and business managent. With great case studies in order to understand how to apply these techniques on the real world.
14. Inductive Logic Programming Techniques and Applications
    An old book about inductive logic programming with great theoretical and practical information, referencing some important tools.
15. An Introduction to Data Science
    An introductory level resource developed by a american university with to objective to provide solid opinions and experience about data sciences.

Originally posted by Prof. Dr. rer. nat. Stephan Trahasch in his web site.