Digital Teaching
Additional information is found on the following web site: [url]https://www.rmr.tu-darmstadt.de/lehre_rmr/lehrveranstaltungen_rmr/machine_learning_rmr/index.de.jsp[/url]
Course Contents
[list]
[*]Concepts of machine learning
[*]Linear methods
[*]Support vector machines
[*]Trees and ensembles
[*]Training and assessment
[*]Unsupervised learning
[*]Neural networks and deep learning
[*]Convolutional neuronal networks (CNNs)
[*]CNN applications
[*]Recurrent neural networks (RNNs)
[/list]
Literature
[list]
[*]T. Hastie et al.: The Elements of Statistical Learning. 2. Aufl., Springer, 2008
[*]I. Goodfellow et al.: Deep Learning. MIT Press, 2016
[*]A. Géron: Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow. 2. Aufl., OReilly, 2019
[/list]
Preconditions
Fundamental knowledge in linear algebra and statistics
Preferred: Lecture Fuzzy logic, neural networks and evolutionary algorithms
Online Offerings
moodle
Additional information is found on the following web site: [url]https://www.rmr.tu-darmstadt.de/lehre_rmr/lehrveranstaltungen_rmr/machine_learning_rmr/index.de.jsp[/url]
Course Contents
[list]
[*]Concepts of machine learning
[*]Linear methods
[*]Support vector machines
[*]Trees and ensembles
[*]Training and assessment
[*]Unsupervised learning
[*]Neural networks and deep learning
[*]Convolutional neuronal networks (CNNs)
[*]CNN applications
[*]Recurrent neural networks (RNNs)
[/list]
Literature
[list]
[*]T. Hastie et al.: The Elements of Statistical Learning. 2. Aufl., Springer, 2008
[*]I. Goodfellow et al.: Deep Learning. MIT Press, 2016
[*]A. Géron: Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow. 2. Aufl., OReilly, 2019
[/list]
Preconditions
Fundamental knowledge in linear algebra and statistics
Preferred: Lecture Fuzzy logic, neural networks and evolutionary algorithms
Online Offerings
moodle
- Lehrende: Michael Vogt
Semester: ST 2022