Learned statistics
Started working on Statistical Learning - STATSX0001 course by Stanford ( edX )

Few notes: 
  1. The introduction is very friendly and starts explaining how we got from Statistics to Machine Learning as a profession when both are intimately related. 
  2. Second lesson is an intro about regression models, how you go to predict a quantity based on a series of predictors, and this comes out based on a function of those predictors. 
  3. Ultimately the prediction is about doing an estimation about the function and this estimation contains errors, as it's not always perfect.
  4. There are 2 types of errors, one that can be reduced by adjusting the estimation f^(x) and an error which is called irreducible error, which it doesn't matter how well our estimator function is, there is always an amount called epsilon that we won't be able to eliminate.