Reading List on Algorithms, Machine Learning, Text Mining, Statistics, Java and Mathematics

I will be updating the below mentioned list often.
The following list, detail books that i have read or intend to read. The books that i have read and found them to be a good supplement for this topic have my comments. The books that i have yet to read just have their titles without my comments on it.
1. Causality: Models, Reasoning and Influence authored by Judea Pearl, 6th ed, Cambridge University Press Publication, Link is the Google book version of it
2. Data mining: Concepts and Techniques authored by Huan, Jiawei & Kambler, Micheline 2nd ed, Waltham USA: Morgan Kaufmann
3. Data mining: Practical machine learning tools and techniques, authored by Ian Witten et al, 3rd ed, Morgan Kaufmann USA
4. Data mining: A knowledge discovery approach authored by Cios, Krzysztof et al, 2007, Springer Pub.
5. Machine Learning authored by Tom Mitchell- a one stop guide for undergraduate and postgraduate students even novices who want to unravel the mysteries proffered by machine learning, In short a must read book.
6. Watch John Elder presenting short tutorials on Data Mining
7. Tree based classification and Rule based classification technique are methods that would classify entities (like students) on their choice of a particular course. Good Forum Link
8. Statistical Data Mining Tutorial by Andrew Moore- a must read, very well described.
9. Think Bayes- Bayesian Statistics made simple– Now this is a free online version, a good book on Bayes algorithm with implementation in Python language
10. Open Intro Statistics– another good free e-book on statistics that explains concepts from the beginning with simplicity and ease
11. A First Encounter with Machine Learning– a must read for all data scientists interested in machine learning
12. A Programmer’s Guide to Machine Learning– An online book lucidly written and replete with examples, must read