How to Learn #MachineLearning: Advanced Statistics

When I first discovered the topic of #MachineLearning I was very excited about all the use cases and possible implementations.

I knew it was a very broad topic so I decided to break it down into parts and one of the first sub-topics that I wanted to learn was STATISTICS.

So I decided to join advanced stats courses during my master´s degree at Monash University.

I remember that my first day of the lectures was quite intimidating, they told me we were going to learn about Regularisation, Probabilistic Inference, Model Selection and Density Estimation.

We were going to be using #R and #Python.

We were going to do some practical projects regarding something called bayesian data analysis, using industry problems and try to solve them from a data science and statistical point of view.

It was quite intimidating.

Most of my peers were data analysts, aspiring data scientists and had a strong background in IT, programming, mathematics and even astrophysics.

I knew these courses were going to be quite challenging so I decided to start doing self-learning during my weekends and after classes using library materials online courses and blogs (link below)