Lehrinhalte
The course covers the following topics:
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[*]Python programming basics
[*]Data science introduction
[*]Data storage and formats
[*]Data exploration and visualization
[*]Statistical methods and inference
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[*]Descriptive statistics (uni & bivariate)
[*]Inferential statistics
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[*]Feature extraction
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[*]Time Series Data
[*]Image data
[*]Audio data
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[*]Statistical learning
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[*]Cross-validation, overfitting, annotation
[*]Regression
[*]Classification
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Literature
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[*]Lecture notes and slides can be downloaded here:
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[*][url]http://www.spg.tu-darmstadt.de[/url]
[*]moodle
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[*]Further reading:
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[*]Wes McKinney: Python for Data Analysis, O’Reilly, 2017
[*]Christopher M. Bishop: Pattern Recognition and Machine Learning, 2011
[*]James, Witten, Hastie and Tibshirani, Introduction to Statistical Learning, Springer, 2017
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Semester: Verão 2022