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https://github.com/mirtia/02450-introduction-to-ml-dm
This repository contains the course's project and notes for the final exam.
https://github.com/mirtia/02450-introduction-to-ml-dm
Last synced: 6 days ago
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This repository contains the course's project and notes for the final exam.
- Host: GitHub
- URL: https://github.com/mirtia/02450-introduction-to-ml-dm
- Owner: Mirtia
- License: mit
- Created: 2024-02-12T07:09:12.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2024-04-11T10:57:53.000Z (7 months ago)
- Last Synced: 2024-04-11T11:48:51.389Z (7 months ago)
- Language: Jupyter Notebook
- Size: 7.76 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# 02450-Introduction-To-ML-DM
This repository contains the course's project and notes for the final exam.
## Structure
```sh
.
├── analysis.ipynb
├── data
│ ├── SAheart.csv
│ └── SAheart.md
├── figures
├── LICENSE
└── README.md
```
## TODOs
- [X] The code I put on analysis is still on experimental stage. I gathered some scripts I already have.
- [ ] We have to work on the interpretation of the PCAs and check it furtherly.
- [ ] Add the p-value distribution statistics in the overleaf.
- [ ] Plot projections on 3D and 2D.
- [ ] Add the skewness on the dataset before the analysis.
- [X] Normalize score of atype (0 - 1)
## Requirements
```sh
pip install -r requirements.txt
```