https://github.com/muthu-kumar-u/ml-flower-classification
This repository contains a machine learning project for classifying the Iris dataset using multiple algorithms. It includes data preprocessing, model training, and evaluation. The project supports various algorithms, providing a comparison of performance, and automates workflows for model release and deployment.
https://github.com/muthu-kumar-u/ml-flower-classification
classification fastapi machine-learning ml
Last synced: about 1 month ago
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This repository contains a machine learning project for classifying the Iris dataset using multiple algorithms. It includes data preprocessing, model training, and evaluation. The project supports various algorithms, providing a comparison of performance, and automates workflows for model release and deployment.
- Host: GitHub
- URL: https://github.com/muthu-kumar-u/ml-flower-classification
- Owner: muthu-kumar-u
- License: mit
- Created: 2024-12-31T10:19:48.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-12-31T15:02:05.000Z (over 1 year ago)
- Last Synced: 2025-03-21T08:19:15.352Z (over 1 year ago)
- Topics: classification, fastapi, machine-learning, ml
- Language: Jupyter Notebook
- Homepage:
- Size: 42 KB
- Stars: 2
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# ML Classification: With Iris Dataset
This project trains and evaluates ML models on the Iris dataset. It includes workflows to release trained models.
## Features
- Preprocessing pipeline
- Model training and evaluation
- Automated GitHub Actions workflow for software release
- Iris dataset included
## Getting Started
1. Clone the repository:
```bash
git clone https://github.com/yourusername/ml-project.git
2. Install Dependencies:
```bash
pip install -r requirements.txt
3. Run the main.py:
```bash
python main.py
## Note
- The Iris dataset is included in the repository and will be used during the preprocessing, training, and evaluation phases.