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Machine Learning for Engineers; Introduction to Methods and Tools (MLE)5 ECTS (englische Bezeichnung: Machine Learning for Engineers; Introduction to Methods and Tools)
Modulverantwortliche/r: Björn Eskofier Lehrende:
Björn Eskofier, Jörg Franke, Nico Hanenkamp
Startsemester: |
WS 2020/2021 | Dauer: |
1 Semester | Turnus: |
halbjährlich (WS+SS) |
Präsenzzeit: |
0 Std. | Eigenstudium: |
150 Std. | Sprache: |
Englisch |
Lehrveranstaltungen:
Inhalt:
This course offers an overview of some of the most widely used machine learning (ML) methods that are required for solving data science problems. We present the necessary fundamental for each topic and provide programming exercises.
The course includes:
1) The common practices for data preGprocessing.
2) Teaching different tasks regarding regression, classification, and dimensionality reduction using methods including but not limited to linear regression and classification, Support vector machines and Deep neural networks.
3) Introduction to Python programming for data science.
4) Applying machine learning models on real world engineering applications.
Lernziele und Kompetenzen:
Literatur:
Machine Learning: A Probabilistic Perspective, Kevin Murphy, MIT
press,2012
The Elements of Statistical Learning: Data Mining, Inference, and Prediction,
Trevor Hastie, Robert Tibshirani, Jerome Friedman, Springer, 2009
Deep Learning, Ian Goodfellow and Yoshua Bengio and Aaron Courville,
MIT Press, 2016
Studien-/Prüfungsleistungen:
Machine Learning for Engineers - Introduction to Methods and Tools (Prüfungsnummer: 50671)
- Prüfungsleistung, Klausur, Dauer (in Minuten): 90, benotet, 5 ECTS
- Anteil an der Berechnung der Modulnote: 100.0 %
- Prüfungssprache: Englisch
- Erstablegung: WS 2020/2021, 1. Wdh.: SS 2021
1. Prüfer: | Björn Eskofier |
- Termin: 24.07.2021, 10:15 Uhr, Ort: K1, H7, H11
Termin: 19.02.2022, 11:00 Uhr, Ort: BASPH
Termin: 06.08.2022, 10:00 Uhr, Ort: StudOn Exam
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UnivIS ist ein Produkt der Config eG, Buckenhof |
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