Machine Learning for Scientific Applications
Machine learning is a subset of Artificial Intelligence algorithms that automatically learns from past data without programming explicitly. In this 10 hours course, we will do a gentle introduction to machine learning through sklearn, a python library that has implemented most of the state-of-the-art algorithms currently used. Finally, we will talk about deep learning, a subset of the machine learning algorithms that are at the core of the current revolution in artificial intelligence. At the end of the course, you will get the basics of machine learning using sklearn and how to create data pipelines to train your algorithms. For the development of this course, we are going to use Google Colab. For this reason, it is recommended to have a google account ready before starting the course.
Information about the teacher:
Albert Mosella-Montoro is a PhD Candidate at Universitat Politècnica de Catalunya under the advisement of Professor Javier Ruiz Hidalgo. He received a degree in Audiovisual Systems Engineering from Universitat Politècnica de Catalunya in 2015, after completing his thesis on object detection in collision path under the advisement of Professor Javier Ruiz Hidalgo. In 2017 he received a Master degree in Computer Vision from Universitat Autònoma de Barcelona, after completing his thesis on vehicle detection using instance segmentation under the advisement of Professor Javier Ruiz Hidalgo and Dr.-Ing Florian Baumman from Adasens Automotive GmbH.
The 2021 Course will take place from May 31st to June 4th 2021, from 10:30h to 12:30h