Experimentation and Evaluation in Machine Learning

General

Author: Aleyna Albayrak

E-Mail: uk076901@student.uni-kassel.de

Institute: Intelligent Embedded Systems, University of Kassel, Germany

This repository was created as part of the course Experimentation and Evaluation in Machine Learning.

Project Structure

• e2ml: Python package of the Python modules implemented during this course
  • evaluation: Python package to evaluate and visualize experimental results
  • experimentation: Python package with methods of design of experiments
  • models: Python package of implement machine learning models
  • preprocessing: Python package of data preprocessing functions
  • simulation: Python package to execute experiments
• notebooks: directory of Jupyter notebooks with example code
  • tutorial_python_solutation.ipynb: introduction into Python including important modules, such as, NumPy, SciPy, and Scikit-learn
• LICENSE: information about the terms under which one can use this package
• setup.py: Python file to install the project's package

Setup

To install and use this project, one needs to consider the following steps.

1. Update the general section of README.md and the setup.py file by adding your credentials to the designated text passages.
2. Install conda for Python 3.9 according to the installation guide.
3. Create a conda environment with the name e2ml-env.

conda create --name e2ml-env python=3.9

4. Activate the created environment.

conda activate e2ml-env

5. Install the project's package e2ml in the conda environment.

pip install -e .

6. Now, you have installed the Python package e2ml and should be able to use it. You can test it by importing it within a Python console.

import e2ml

7. Finally, you can start to work with this project. In particular, you can view the Jupyter Notebooks in the folder notebooks by executing the following command.

jupyter-notebook

Experimentation

TBD

Evaluation

TBD

Results

TBD