Please recommend books on calculus, linear algebra, statistics for someone trying to learn Probability Theory and Machine Learning? I am tackling some topics in Probability Theory and Machine Learning and while I have plenty of resources dedicated to those disciplines I am lacking in a good basic math foundation.
Does anyone know any good, concise math books that can help introduce the foundations (calculus, linear algebra, statistics) of these disciplines to someone whose exposure to math is very limited?
Of particular interest would be a book that could relate these concepts to someone familiar with programming to leverage that mode of thinking to relate the essential ideas.
 A: For Calculus: I would use the standard textbook for U.S colleges: 
 Calculus: Early Transcendental
For Linear Algebra:  I highly encouraged you to check out Professor Gilbert Strang's Introduction to Linear Algebra
supplement with MIT Opencourseware's free Linear Algebra course
There is even a series of video lectures of Professor Gilbert Strang's course on youtube
This is how I taught myself Linear Algebra
For Probability and Statistics: I used Probability & Statistics for Engineers & Scientists for my introduction class during sophomore year.  If you REALLY want to understand probability theory, I cannot recommend Probability Theory: The Logic of Science enough.  It is hand down one of the best books I've ever read.  You will be a master at Probability Theory after reading it.  
By the way all these textbooks are available online as pdf versions at a website called Library Genesis
A: You may want to try someone online videos that may be helpful. 
Here is link for free linear algebra book with solutions
http://joshua.smcvt.edu/linearalgebra/
