Summer School 2021 - Introduction to Statistical Machine Learning

September 06 - 09, 2021, Online event

BINARY Project Logo

The 2021 joint Summer School of the BINARY and EAI Project will feature an introduction to statistical machine learning techniques. The target audience are graduate / PhD students and researchers who are still beginners in machine learning and Bayesian data analysis.

Preliminary Program

 MondayTuesdayWednesdayThursday
14:15 - 15:45
Intro,
Inductive Reasoning,
Bayesian Statistics
Classical Machine
Learning Algorithms
Deep LearningThe Small Data
Challenge I
15:45 - 16:15Discussion &
Coffee-Break
Discussion &
Coffee-Break
Discussion &
Coffee-Break
Discussion &
Coffee-Break
16:15 - 17:45Information Theory,
Machine Learning
Basics
Learning Theory,
Generalization,
MDL-Principle
Advanced
Deep Learning
The Small Data
Challenge II
17:45 - 18:15Discussion &
Coffee-Break
Discussion &
Coffee-Break
Discussion &
Coffee-Break
Discussion &
Coffee-Break
Each Session consists of 60min lecture and 30min hands-on tutorials.

Lecturers & Tutors

Steffen Albrecht, Susanne Gerber, Illia Horenko, Stanislav Sys, Michael Wand, Stephan WeiƟbach

Prerequisites

Basic mathematics (statistics, calculus, linear algebra), python programming (tutorials).

Registration

The School is open to all JGU researchers and collaborators.
To register, please send an email to Cosima Caliendo at emergent-ai@uni-mainz.de until August 22, 2021.

Participation

The school will be held virtually on MS-Teams. Within JGU-Teams you can join via "discover new Teams" with access code "avbdbck".