Machine Learning Times
Machine Learning Times


The Hardest Parts of Data Science

 Contrary to common belief, the hardest part of data science isn’t building an accurate model or obtaining good, clean data. It is much harder to define feasible problems and come up with reasonable ways of measuring solutions. This post discusses some examples of these issues and how they can be addressed. The not-so-hard parts Before

The Data Behind Data Scientists: Top Kaggle Performers

 Kaggle, an online platform that hosts data analytics competitions, allows companies to tap into the expertise of data gurus to tackle specific company issues (and possibly reap prizes and job offers, if successful). With more than 100,000...

A Good Business Objective Beats a Good Algorithm

 Predictive Modeling competitions, once the arena for a few data mining conferences, has now become big business. Kaggle ( is perhaps the most well-known forum for modeling competitions, using a crowd-sourcing mentality: if more people try to...