How I got started with AI

I am a member of the Artificial Intelligence and Robotics Group in UTN - Buenos Aires, Argentina, and I’m working on a BCI project.

I am interested in Machine Learning algorithms, and I found several types of implementations across the web, that I tried and coded. I am by no means an expert, just an enthusiast.

K-NN Algorithm.

The K- Nearest Neighbour is one of the simple yet powerful algorithms, and I first encounter it when I was reading about swarm intelligent, and later, about Ant Colony Simulation.

One of the uses of this type of simulations is related to the Travelling Salesman Problem, and I found a nice example using a NBA dataset. Click on the title for a more complete description.

Linear Regression with One Variable

Another simple algorithm, this time for the use of prediction. Actually, this example is taken from the Coursera course Machine Learning, a great place to start by the way. In this case, I translate the code from Matlab to Python. Click on the title for a more complete description.

Recommender Systems

In ECI’s courses of 2016, I was lucky enough to get a spot on the lecture of Carlos Castillo: Data Mining in Graphs and Social Media. It was a great introduction and here you can check out my graded work about Facebook.

This motivated my curiosity about Recommender Systems and how it works, so I begin searching about movie ratings. This is how a found out about the MovieLens page and furthermore, about the GroupLens research lab.