Objectives
Learning outcomes are:
- learn the fundamentals of machine learning
- obtain basic understanding of supervised classification
- learn support vector machines and apply them to datasets
Attendees do not need to prepare any software before the start of the course, as the course progresses through the lessons, we will create scripts step-by-step together and when needed, you will be pointed to download sites.
Requirements
Specific prerequisites:
In order to be able to benefit from this course, you need to be able to perform on the following level:
- using UNIX scripts (important)
- using batch systems on supercomputers (less important)
- have basic understanding of linear algebra (less important)
Attendees will need to bring their own laptops
Materials
INTELLECTUAL PROPERTY RIGHTS NOTICE:
• The User may only download, make and retain a copy of the materials for his/her use for non‐commercial and research purposes.
• The User may not commercially use the material, unless has been granted prior written consent by the Licensor to
do so; and cannot remove, obscure or modify copyright notices, text acknowledging or other means of identification or disclaimers as they appear.
• For further details, please contact BSC‐CNS education [at] bsc [dot] es