From Machine Learning to Deep Learning: A concise introduction

Description

Registration

https://regi.hlrs.de/2023/DL-HLRS/registration

The course

This HLRS course addresses students, data scientists, and researchers who would like to have an introduction to Machine and Deep Learning methods to solve challenging and future-oriented problems. Both Machine and Deep Learning methods and examples as well as a method for data compression will be presented. Different examples are shown via hands-on sessions on an HLRS cluster. However, please be aware that this course is not a sequence of beginners’-to-advanced lectures about theoretical aspects of AI.

Data Compression on Day 3

Given the deluge of information needed to power machine and deep learning methods, it is imperative to think about effective data processing strategies. Therefore, the course will conclude with an introduction to data compression using the BigWhoop library (developed within EXCELLERAT P2). As an efficient data reduction tool, BigWhoop can be applied to generic numerical datasets to minimize I/O bottlenecks and optimize data storage.

 

Web-url: https://www.hlrs.de/training/2023/dl-hlrs
Presenters: Khatuna Kakhiani (HLRS)Patrick Vogler (HLRS)Lorenzo Zanon (HLRS)Anna Schwarz (University of Stuttgart - IAG)
Online: Yes