if you want to move beyond an introduction and learn all the gory mathematical detailsthen machine learninga probabilistic perspectivek murphythe mit pressis an excellent option it is very recent (published in )and contains the cutting edge of ml research this , page book can also serve as referenceas very little of machine learning has been left out & sites the following are the two & websites of machine learningmetaoptimize ( & website where many very knowledgeable researchers and practitioners interact cross validated (statistics & sitewhich often features machine learning questions as well as mentioned in the beginning of the bookif you have questions specific to particular parts of the bookfeel free to ask them at twotoreal (jump in and help as best as we can blogs the following is an obviously non-exhaustive list of blogs that are interesting to someone working on machine learningmachine learning theory at degdeg this is blog by john langfordthe brain behind vowpal wabbit (degdeg the average pace is approximately one post per month the posts are more theoretical they also offer additional value in brain teasers text and data mining by practical means at blogspot de degdeg the average pace is one per monthwhich is very practical and has always surprising approaches blog by edwin chen at degdeg the average pace is one per monthproviding more applied topics