Dive into machine learning and deep learning
techniques and apply them to real life datasets!

This workshop is intended as an opportunity to get an overview on the basics of "applied machine learning" techniques. It targets people with a begginer/intermediate level of expertise, and much curiosity! You will put in practice your understanding with few applications of increasing complexity. The workshop will proceed through an intuition-based understanding of the key aspects of machine learning concepts, moving to hands-on exercises on simple datasets using a set of tools needed in any "data scientist virtual backpack".

Find below more information on the workshop - for anything else please refer to the official ISGC 2021 web site

Pre-requisites

This course is intended for learners. A basic Python and/or programming background is needed. Minimal statistics background is expected. Just join us with a PC/laptop, no need to install anything in advance. A quick overview on basic libraries and selected ML frameworks will be given (see "Tools" on the right-hand side), but time is short! so any previous knowledge would be a plus.

Tools

The primary language will be Python via Jupyter notebooks hosted on Google colab . A (quick!) overview on e.g. Numpy, Pandas, Matplotlib will be given. The primary ML/DL libraries and frameworks of which we will use some functionalities will be Scikit-learn, Tensorflow and Keras.

Material

Selected material from the classes - both slides and code - will be available to attendees. Details at the workshop.

Connection details

For all information about how to connect online to the workshop, please refer to the official ISGC 2021 web site.

Timetable and Program

The workshop will take place on Monday 22 March 2021, 09:00 - 17:00 CET. .

Check out a detailed calendar in the link below.

Explore ISGC 2021!

Apart from the ML workshop, the International Symposium on Grids & Clouds 2021 (ISGC 2021) has a rich program, covering a variety of topics around the main theme: Challenges in High Performance Data Analytics: Combining Approaches in HPC, HTC, Big Data and AI.

Explore the entire Conference program at the link below.