machined learnings at degdeg flowingdata at degdeg the average pace is one per monthcovering theoretical discussions of practical problems although being more of statistics blogthe posts often intersect with machine learning simply statistics at degdeg the average pace is one per daywith the posts revolving more around statistics normal deviate at degdeg the average pace is one per monthproviding more applied topicsoften revolving around learning big data there are several posts per monthfocusing on statistics and big data statistical modelingcausal inferenceand social science at andrewgelman com degdeg there is one post per day with often funny reads when the author points out flaws in popular media using statistics data sources if you want to play around with algorithmsyou can obtain many datasets from the machine learning repository at university of california at irvine (uciyou can find it at getting competitive an excellent way to learn more about machine learning is by trying out competitionkaggle (and has already been mentioned in the introduction on the websiteyou will find several different competitions with different structures and often cash prizes the supervised learning competitions almost always follow the following formatyou (and every other competitorare given access to labeled training data and testing data (without labelsyour task is to submit predictions for the testing data when the competition closeswhoever has the best accuracy wins the prizes range from glory to cash