This lecture follows up on Programming in Python I and shall enable the students to solve more complex scientific tasks in the area of machine learning (ML) and AI. After completing the course, students will be able to realize ML projects, including the implementation of data preparation, data (pre)processing pipelines, neural network architectures, model training, and model evaluation, in Python.
Subject
Realization of a machine learning project in Python
Data preparation
Fast data (pre)processing in Python
Implementation of different neural network architectures
Training of neural network models
Evaluation of neural network models
Optimizing Python code
Pytorch/Tensorflow (CPU/GPU computation for machine learning and AI)
Criteria for evaluation
Online Exams
Language
English
Changing subject?
No
Corresponding lecture
in collaboration with 536COSCPP2U20: UE Programming in Python II (1.5 ECTS) equivalent to 536COSCPP2K19: KV Programming in Python II (3 ECTS)
