The algorithm design manual is really nice in that it provides a mapping from problems to algorithmic approaches. I was wondering if there is something similar, specifically, for machine learning problems.
Have you seen this -> <a href="http://peekaboo-vision.blogspot.com/2013/01/machine-learning-cheat-sheet-for-scikit.html" rel="nofollow">http://peekaboo-vision.blogspot.com/2013/01/machine-learning...</a> ... Specifically the image at <a href="http://1.bp.blogspot.com/-ME24ePzpzIM/UQLWTwurfXI/AAAAAAAAANw/W3EETIroA80/s1600/drop_shadows_background.png" rel="nofollow">http://1.bp.blogspot.com/-ME24ePzpzIM/UQLWTwurfXI/AAAAAAAAAN...</a> It seems like a good start.<p>There are myriad resources but none that I can think of that cover all the different problem types.<p>What are you interested in specifically?
There is another book written by the same author specifically aimed at Data Science problems, called 'The Data Science Design Manual'.
Check it out at its dedicated website: www.data-manual.com