I am an undergraduate student studying mathematics and microbiology. I recently got a research project to study the evolution of viruses from the computational perspective, particularly from machine learning, where I would like to use it to predict the future viral strains. Unfortunately, I am very new to machine learning, so I would like to seek your advice on some books to start learning machine learning; it would be great if you can recommend one introductory book on ML and one comprehensive, detailed reference on ML. My plan is to learn ML with those books and conducting my research (I learn best when I have a specific project/problem to pursue). My preferred programming languages are R and C/C++.
My background: real analysis, number theory, point-set topology, axiomatic set theory, and theoretical linear algebra. I am currently learning representation theory and algebraic topology. I have not taken a mathematical statistics course, but I am willing to learn the necessary concepts alongside with studying the ML.
Unfortunately, I have not found any ML book that focuses on biological applications, so I welcome any recommendations you have on an elementary book and a comprehensive, detailed reference on ML.
Best Answer
If you like Python or Java, you may consider the book "Numeric Computation and Statistical Data Analysis on the Java Platform" by Chekanov http://www.springer.com/us/book/9783319285290 It describes the DMelt (http://jwork.org/dmelt/) platform. There is dedicated section in this book on machine learning.