Miguel F Alarcon

Computer scientist and mathematician. Interested in Machine learning as a means to an end. I love all the opportunities it enables, not in one industry, but across all.

Studied Computer Science and Mathematics at Universidad Autónoma de Madrid. Spent a year studying abroad in Copenhagen and then worked for three months in the Data Science department of a cyber security company.

I finished my studies the following year and went straight to Barcelona to start my job for The Hotels Network, where I have helped build the data, models and experiments platform, as well as build various data science products such as user-behavior predictive models, recommendations models and so on. Lately I've grown an interest into causality, and how it can help us model the world.




Introducción a la causalidad en Python
Miguel F Alarcon

Todos sabemos que correlación no es igual a causalidad. La mayoría de modelos de Machine Learning en la actualidad buscan correlaciones de los datos con el objetivo. La causalidad viene como herramienta para identificar los factores que afectan al objetivo y de qué manera lo hacen.
El objetivo de esta charla es proporcionar unos conocimientos básicos, así como las herramientas para poder solucionar problemas de inferencia y modelado causal en Python.

Data Science, Machine Learning and AI
Ada Lovelace (Paraninfo)