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.
Session
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.