Table of Contents
1
Data Analysis and Machine Learning with Python
1.1
Information on this course
1.2
Contents
Data Analysis and Machine Learning with Python
¶
Lecturers:
Günter Duckeck, Nikolai Hartmann, Alexander Mann
Dates:
5 days, 25.09.2023 -- 29.09.2023, 10:00 -- 12:00 & 13:30 -- 16:00
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ZOOM link: see link above
Information on this course
¶
Formalities and course outline
(html)
References and Literature
The
Technical Hints
(html)
explain how to download and setup the repository.
Contents
¶
Introduction
Organizational issues
References
Python setup
jupyter notebooks
Python introduction:
link to material Software Handwerkszeug Course
Scientific Python:
Numpy
Matplotlib
SciPy
SymPy
Pandas - data analysis with Python
Awkward array
Exercises
,
SIR model
Statistics:
Basic Concepts
Random Numbers
Fitting
Machine learning
Basic concepts
Introductory example -
Nearest neighbours
Scikit-learn Overview
Testing, validating, Overtraining
Decision Trees
Rescaling data
Exercises:
on Rotated Decision Trees
further suggestions
Neural Networks
Neural Nets Introduction
Neural Nets from Scratch
Advanced ML
Neural Nets with Tensorflow/Keras
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