Course/Event Essentials
Event/Course Start
Event/Course End
Event/Course Format
In person
Primary Event/Course URL
Training Content and Scope
Scientific Domain
Technical Domain
Level of Instruction
Beginner
Intermediate
Advanced
Other
Sector of the Target Audience
Research and Academia
Industry
Public Sector
Other (general public...)
HPC Profile of Target Audience
Application Users
Application Developers
Data Scientists
System Administrators
Language of Instruction
Other Information
Organiser
Supporting Project(s)
EuroCC2/CASTIEL2
Event/Course Description
Would you like to learn the basics about Deep Learning?
What?
On day 1 of this course you will:
- Understand the fundamental theories of machine learning and the intuitions/ideas behind the algorithms
- Work with a high-level machine learning API (Keras)
- Explore hyperparameter space to improve a neural network
- Understand the pitfalls of classic machine learning algorithms
On day 2 of this course you will learn:
- How to set up your software environment
- About the technical capabilities of modern day CPUs and GPUs
- How to identify bottlenecks in your code
Who?
Everyone interested in getting familiar with machine learning at scale, from the beginning up to more advanced topics
Prerequisites
- Basic knowledge on statistics
- Basic knowledge on linear algebra
- Basic knowledge on Python programming. Some experience with the use of Jupyter Notebooks is desirable, but not essential.
* Basic knowledge on parallel computing is helpful, but not required.