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 Weißbach

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".