If Your Data Is Bad, Your Machine Learning Tools Are Useless by Thomas C. Redman via @HarvardBiz

Poor data quality is enemy number one to the widespread, profitable use of machine learning. While the caustic observation, “garbage-in, garbage-out” has plagued analytics and decision-making for generations, it carries a special warning for machine learning.

Very good advice in this article that I think should be bookmarked or notes should be taken because you really need to be following these steps if you want to be successful with machine learning.