Zusatz | Introduction to machine learning with Python

Veranstaltungsdetails

Lehrende: Thomas Heil

Veranstaltungsart: Seminar und praktische Übungen

Orga-Einheit: Transformation Management in Digital Societies

Anzeige im Stundenplan:

Semesterwochenstunden: 3

Credits: 2,5

Standort: Campus der Zeppelin Universität

Unterrichtssprache: Englisch

Min. | Max. Teilnehmerzahl: 5 | 24

Prioritätsschema: Standard-Priorisierung

Inhalte:
The course aims to provide students with a first introduction to machine learning with python. People without prior knowledge in Python can contact me for material to learn the Python basics prior to the course. 

1. Introduction to Python 

Why machine learning with Python?

- Brief renewal of Python basics 

2. Introduction to Machine Learning

- Idea
- Difference to classical statistical thinking
- Data pre-processing

3. Regression and LASSO

- Short introduction to regression
- From Regression to LASSO

4. Classification

- K-Nearest- Neighbors
- Decision Trees, Random Forests

5. Neural Networks

- Brief introduction to neural networks


6. Miscellaneous

- (unsupervised learning / clustering)
- (natural language processing)

6. Class Project

- TBD

Lernziele:
At the end of the course, students gained the ability to learn machine learning for Python further on their own. Also students have the knowledge to start first small projects on their own.

Weitere Informationen zu den Prüfungsleistungen:
The exam is a Python programming project. Students can chose and adjust projects to their liking.

Literatur:
Literature on learning Python is vast. For the brief introduction to Python we won't follow a specific textbook. However, the Python homepage offers some proposals:

https://wiki.python.org/moin/IntroductoryBooks

Modulbeschreibung:


Note: instructions on installing Python and a Python Distribution (Anaconda) will be available on ILIAS some days before the course starts. All students are kindly asked to install the required software before the course, as there is no time within the lecture. You are always warmly invited to contact me via E-Mail if a problem while the installation occurs.

Note further: the course language is english.

Wenn Sie E-Learning Funktionalitäten nutzen möchten, tragen Sie bitte "Ja" ein.:
ja

Termine
Datum Von Bis Raum Lehrende
1 Fr, 10. Nov. 2023 13:30 18:00 Fab 3 | 2.08 Thomas Heil
2 Sa, 11. Nov. 2023 10:00 14:00 Fab 3 | 2.08 Thomas Heil
3 Fr, 24. Nov. 2023 13:30 18:00 Fab 3 | 2.08 Thomas Heil
4 Sa, 25. Nov. 2023 10:00 18:00 Fab 3 | 2.08 Thomas Heil
Veranstaltungseigene Prüfungen
Beschreibung Datum Lehrende Bestehenspflicht
1. Teilnahme | Class Participation ohne Termin Nein
Übersicht der Kurstermine
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Lehrende
Thomas Heil