Python Videolectures and Tutorials
Location & Time
The exercise is based on multiple short (typically 2-4 pages) assignments. For most assignments a written report in Latex and Python Code has to be submitted via Email. Each student has to submit an individual assignment report and code.
The topics of the assignments are
- Creating Latex Documents & Data handling (Latex env. setup, report template, reading & editing data files),
- Programming in Python & Probability Theory (Python basics, Editor PyCharm, Workflow, variables, functions, classes, plotting, Gaussian distributions, sampling, plotting),
- Linear Probabilistic Regression (features, least-squares regression derivation & implementation, regularization),
- Nonlinear Probabilistic Regression (Gaussian Processes, implementation, kernels, predictions),
- Probabilistic Time-Series-Models (Implementation & Learning from real-world data, Visualization, Predictions).
Learning objectives / qualifications
Hands-on experience with machine learning methods.