Methods of data analysis II & Introduction to machine learning (PW-MoDA)5 ECTS
(englische Bezeichnung: Methods of data analysis II & Introduction to machine learning)
(Prüfungsordnungsmodul: Methods of data analysis II and Introduction to machine learning)

Lehrveranstaltungen:

• • Methods of data analysis II & Introduction to machine learning
    (Vorlesung, 2 SWS, Stefan Funk et al., Mi, 10:00 - 12:00, SRTL (307))
  • Methods of data analysis II & Introduction to machine learning (exercise class)
    (Übung, 2 SWS, Stefan Funk et al., Di, 14:15 - 15:45, CIP-Pool in der Physik)

Inhalt:

Contents:
The lectures provide an introduction to machine learning methods and their application to problems in physics.
The topics of the lectures include:

• Bayesian statistics, inference

• Linear regression

• Logistic regression

• Regularization

• Trees

• Clustering

• Model selection: bias-variance trade off

• Perceptron

• Markov chain Monte Carlo

• Introduction to deep learning

Lernziele und Kompetenzen:

Learning goals and competences:
Students

• explain the relevant topics of the lecture

• apply the methods to specific examples

Literatur:

Trevor Hastie et al.: The Elements of Statistical Learning

Bemerkung:

May be applied to specialisation 'Astrophysics and astroparticle physics' in the physics master program starting winter term 2018/19.

Organisatorisches:

Useful prerequisites: Methoden der Datenanalyse I and basic knowledge of Python programming.

Studien-/Prüfungsleistungen:

Methods of data analysis II & Introduction to machine learning (Prüfungsnummer: 997394)

(englischer Titel: Methods of data analysis II & Introduction to machine learning)

Prüfungsleistung, Klausur, Dauer (in Minuten): 90, benotet, 5 ECTS

Anteil an der Berechnung der Modulnote: 100.0 %

Prüfungssprache: Englisch

Erstablegung: WS 2019/2020, 1. Wdh.: WS 2019/2020 (nur für Wiederholer)

1. Prüfer:

Stefan Funk

1. Prüfer:

Dmitry Malyshev