….
Research & Teaching
about SUPERCOMPUTING & ARTIFICIAL INTELLIGENCE
Professor at UPC Barcelona Tech
Research Manager at Barcelona Supercomputing Center
FEATURED INFORMATION
NUEVO LIBRO EN CASTELLANO
SOBRE aprendizaje por refuerzo
INTRODUCCIÓN AL APRENDIZAJE POR REFUERZO Teoría y práctica en python
Deep Reinforcement Learning Explained
A series that gradually and with a practical approach will be introducing the reader in this exciting technology of Deep Reinforcement Learning.
Without the Rise of Supercomputers There Will Be No Progress in Artificial Intelligence
We need solutions that overlap these two research worlds Although artificial intelligence (AI) research began in the 1950s, and the fundamental algorithms of neural networks were already known in the last century, this discipline was left dormant for many years due to the lack of results that could excite both academia and the industry. Artificial Intelligence
Practical Introduction to Programming Deep Learning on a Supercomputing
Hands-on about how to scale a Deep Learning application in the BSC’s CTE-Power cluster as an activity of the ACM Summer School In the first part of this seminar, we introduced that supercomputers are a key component of the progress of Artificial Intelligence and what drove changes in effective compute over the last years was
How to Take Advantage of the New Disruptive AI Technology Called Transformers
Starting in 2017, Transformers have facilitated impressive progress in the field of deep learning. Many of us consider Transformers to be the most important development in recent years and with the greatest potential in the area. For this reason, I believe that it is worthwhile for us to be watchful of their progress. Transformers were
Deep Reinforcement Learning Explained
Content of this series Towards Data Science This is a relaxed introductory series with a practical approach that tries to cover the basic concepts in Reinforcement Learning and Deep Learning to begin in the area of Deep Reinforcement Learning. UPDATE: Spanish version Part 1: Introduction to Deep Reinforcement Learning 01: A gentle introduction to Deep
How to build a Deep Learning model in 10 lines
Cover photo by Alex Kotliarskyi on Unsplash A Guide to quickly immerse yourself in Deep Learning This post will introduce the reader to the basics of neural networks through a case study that using only 10 lines of Python code creates and trains a neural network that recognises handwritten digits in 3 basic steps: 1-
Cómo construir un modelo Deep Learning en 10 líneas
(tiempo de lectura: 20 minutos) [versión en inglés] [código en GitHub] Guía básica para sumergirse rápidamente en Deep Learning Este post presentará al lector los conceptos básicos de las redes neuronales a través de un estudio de caso que al usar solo 10 líneas de código Python crea y entrena una red neuronal que reconoce