Data Workshop with Vladimir #3

Let me invite you for Data Workshop #3. You can check how it were on previous workshops: Data Workshop #2 - http://www.meetup.com/datakrk/events/231590232/ and Data Workshop #1 - http://www.meetup.com/datakrk/events/230392309/. Let’s focus on very important topic - Evaluating Machine Learning Models. Without understanding this key area rest in ML is useless… really. "We don’t have better algorithms. We just have more data.” (c) Google's Research Director Peter Norvig. And question is - is it an axiom? And how can you carefully check that? In general all machine learning (data science) is about a lot of hypothesizes, but which one is better? Of course you can guess, but the reality is it depends on challenge and this is why you should verify carefully it one by one. And when you understood it, the question is how to verify it properly?