Home » project, Summer 2022 »
Location: Rudower Chaussee 25, Raum 2.207
Time: Tuesdays (Bi-weekly), 13:15pm – 14:45pm
The aim of the lab sessions provides students with the practical implementation of Machine Learning Algorithms. Python is used as the programming language. Main topics include; Getting started with Google Colab, preparing Data, Machine Learning Algorithms- Regression,
Classification and Reinforcement learning.
I recommend the class on Mathematics for Machine and Reinforcement Learning and Markov Decision Processes (M27) by Prof. Dr. Dirk Becherer.
Basic Knowledge of Python.
| Date | Room | Content | Material | Exercise |
|---|---|---|---|---|
| 21.04 | 3.008 | Getting started with colab, python installation, python libraries. | Uploaded on moodle | |
| 3.05 | 2.207 | Methods of ML, Datasets, Data loading for ML projects, Descriptive statistics, Data with Visualization. | Uploaded on moodle | Groups should work on 3 different dataset and perform descriptive and explanatory statistics. |
| 17.05 | 2.207 | Data pre-processing review, Classfying an ML Algorithm, ML Algorithms like Linear Regression, Logistic Regression, Decision Trees, Naive Bayes Algorithm etc with scikit-learn. | Groups should apply different ML algorithms to the 3 datasets with scikit-learn and write up a report for submision. Each group will present on the 31st May. | |
| 31.05 | 2.207 | |||
| 14.06 | 2.207 | |||
| 28.06 | 2.207 | |||
| 12.07 | 2.207 |