However, if you want to really understand how things fit together you're probably best reading one of the standard intro textbooks: Murphy's Machine Learning, Bishop's Pattern recognition and machine learning, Hastie et al's The Elements of Statistical Learning, or Wasserman's All of statistics.
http://www.saedsayad.com/data_mining_map.htm
http://peekaboo-vision.blogspot.co.uk/2013/01/machine-learni...
https://azure.microsoft.com/en-us/documentation/articles/mac...
However, if you want to really understand how things fit together you're probably best reading one of the standard intro textbooks: Murphy's Machine Learning, Bishop's Pattern recognition and machine learning, Hastie et al's The Elements of Statistical Learning, or Wasserman's All of statistics.
Or Barber's textbook, which is freely available online and has some nice mind-maps/concept-maps/trees at the start of each section: http://web4.cs.ucl.ac.uk/staff/D.Barber/pmwiki/pmwiki.php?n=...