Learnings from AI & Machine Learning Conference NIPS 2016

Dec. 22, 2016

NIPS conference has become one of the most important events for machine learning research. With a record participation of more than 6000 attendees this year, the field consolidates its importance in both academia and industry. In this post we will discuss the highlights of this year's NIPS conference.


Lean Startup has been a breakthrough during the last years in the entrepreneurial landscape. But this movement is not only a methodology that can be used to create successful businesses, it can also be applied to other domains like Data Science. In this post, I will discuss how to apply the Lean Startup method to a Data Science project. As an example, I created a project that visualizes all football matches that took place in the UEFA Champions League since 1955.


A Gentle Introduction to Convolutional Neural Networks

Sept. 30, 2016

Convolutional Neural Networks (CNN) are one of the key components in the success of Deep Learning and the new Artificial Intelligence revolution. They are specially advantageous in tasks such as object detection, scene understanding and, recently, natural language processing. In this post I will explain what are CNN, what is the intuition behind them and provide an example of its performance in character recognition.


When to use Deep Learning in a Data Science Problem

Aug. 10, 2016

Deep Learning has been around since 2006 and has produced some of most exciting advances in Machine Learning. However, it is not widely used in the industry by Data Scientists yet. In this post we will discuss this business opportunity and when Deep Learning can be used in a Data Science problem.


How human intelligence works and why that makes us racists

June 25, 2016

Have you ever stopped to think how people can be so stupid? Lately, it looks like the world is going crazy. More and more people are supporting radical views. But this is not new, our history is full of atrocities that can be summarized in one simple reason: hatred of the different. The bad news is that our intelligence is optimized to detect differences. The bigger the difference, the higher the effort our brain makes. And many people don't like efforts.