https://github.com/samashi47/ml-toolkit-project
A general-purpose toolkit for data preprocessing, machine learning modeling, and visualization.
https://github.com/samashi47/ml-toolkit-project
classification data data-preprocessing machine-learning python3 visualization
Last synced: 5 months ago
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A general-purpose toolkit for data preprocessing, machine learning modeling, and visualization.
- Host: GitHub
- URL: https://github.com/samashi47/ml-toolkit-project
- Owner: Samashi47
- License: mit
- Created: 2023-12-22T16:41:17.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2024-06-24T13:48:16.000Z (over 1 year ago)
- Last Synced: 2025-04-12T17:13:05.399Z (9 months ago)
- Topics: classification, data, data-preprocessing, machine-learning, python3, visualization
- Language: Python
- Homepage:
- Size: 368 KB
- Stars: 5
- Watchers: 1
- Forks: 3
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
To start, clone this branch of the repo into your local:
```bash
git clone -b main --single-branch [https://github.com/Samashi47/ML-Toolkit-Project]
```
After cloning the project, activate the env:
```bash
.venv\Scripts\activate
```
You can run the following command to install the dependencies:
```bash
pip3 install -r requirements.txt
```
Then run the main file with the following:
```bash
python main.py
```
> [!IMPORTANT]
> The workflow will be as follows:
>
> After starting the app:
>
> 1. Upload data (.csv/.xls/.xlsx/.xml/.json/.data)
> 2. Process and save changes to DataFrame.
> 3. Visualize your data.
> 4. Choose splitting ratio and random state.
> 5. Choose your target column and split your dataset into training & testing data.
> 1. Choose a ML algorithm.
> 6. Train & test your model and evaluate the results.