Detail

Veranstaltungsdetails | Machine learning

Code Startdatum Enddatum Ort Organisation/Kontakt
OT-SC-WS-03| 20.10.-21.10.2021 (9:00-16:00; on each day) | Online via VC 20.10.2021 21.10.2021 Online
Data Train
data-trainprotect me ?!vw.uni-bremenprotect me ?!.de
Freie Plätze Max. Teilnehmer
1 24
ML

Beschreibung

Nowadays, machine learning is everywhere: old and new questions, problems and challenges are tackled with machine learning, sometimes with great success, sometimes not. To successfully use machine learning and understand its limitations, we have to go beyond buzzword bingo and learn the general and basic concepts of machine learning.

Learning contents

This workshop teaches the major concepts of machine learning. We focus on general principles instead of going into full depth of single methods. We will learn the difference between supervised and unsupervised learning, important notation such as models and learners, why training errors are different than test errors and how to optimize and evaluate prediction performance. Nevertheless, the course covers the most important machine learning methods such as k-nearest neighbors, decision trees, random forests, boosting, support vector machines and artificial neural networks. The methods will be introduced in a non-technical and intuitive way. These theory sessions will be complemented by hands-on sessions in R, where the methods are applied in practice.  

Learning outcomes

Understand basic concepts of machine learning:

  • Supervised and unsupervised learning
  • Difference between models and learners, training and test errors, etc.
  • Over- and underfitting
  • Hyperparameter tuning
  • Performance evaluation

Know the major machine learning methods:

  • K-Nearest Neighbors
  • Decision Trees
  • Random Forests
  • Boosting
  • Support Vector Machines
  • Artificial Neural Networks

Be able to perform machine learning analyses in R:

  • Model fitting
  • Hyperparameter tuning
  • Performance evaluation
  • Benchmarking

Visualizing results

Prior knowledge

Advances math is generally NOT required (only for short part on support vector machines); Basic programming skills are required.

Technical requirements

Computer with access to online course platform (RStudio) or with R installed

 (for online format a second screen is advantageous)

Further reading

General introduction:

Advanced:

Additional comments

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    Programm/Ablauf

    Wednesday,  20 October 2021

    9:00-16:00

    Thursday, 21 October 2021

    9:00-16:00