"The difficulty is that machine learning is a fundamentally hard debugging problem. Debugging for machine learning happens in two cases: 1) your algorithm doesn't work or 2) your algorithm doesn't work well enough."
Read it!A journey starting from the standard formulation of linear regression, moving on to the probabilistic approach, and then progressing to Bayesian linear regression.
Read it!A five-step method for transitioning from problem to data-backed decision making.
Read it!