This repository contains a set of exercises for our course ICCD623 Data Mining and Machine Learning 2023-A.
The exercises are designed to reinforce the concepts and techniques learned during the course and provide hands-on practice in Python and R.
Exercises are designed to provide hands-on experience and reinforce the theoretical concepts discussed in the course. Each exercise aims at providing practice and improve students' skills in implementing machine learning algorithms and analyzing real-world datasets.
To work with the exercises in this repository, it is recommended to attend classes in order to have a good understanding of data analysis, as well as strong competence in programming concepts.
The repository is organized as follows:
|-- data
| |-- 01_datamanip
| | |-- Index
| | |-- echocardiogram.data
| | |-- echocardiogram.names
| |-- 02_dataq
| |-- ...
|
|-- notebooks
| |-- 01_DataManip.ipynb
| |-- 02_DataQuality.ipynb
| |-- ...
|
|-- LICENSE
|-- README.md
|-- main.py
|-- requirements.txt
The data directory contains datasets used for our exercises.
The notebooks directory contains the set of Jupyter Notebook files (.ipynb) that solve our Python-based and R-based exercises.
The README.md file provides an overview of the repository and instructions for usage.
The requirements.txt file provides the set of libraries required for both Python and R exercises.
Contributions to this repository, including the addition of new exercises, bug fixes, and improvements, are welcome. If you would like to contribute, please follow the guidelines outlined in the CONTRIBUTING.md file.
This repository is licensed under the MIT License. By contributing to this repository, you agree that your contributions will be licensed under the same license.
The MIT License grants users the freedom to use, modify, and distribute the code and exercises in this repository for both personal and commercial purposes. However, it provides no warranty or liability and requires users to include the original license and copyright notice in any copies or redistributions.
We encourage you to review the full text of the MIT License for more details on your rights and responsibilities.
Please note that any contributions you make to this repository will be subject to the terms of the MIT License. Make sure you are comfortable with these terms before submitting your contributions.
If you have any questions or concerns regarding the licensing or usage of this repository, please feel free to reach out.