https://github.com/dilkushsingh/iris-species-classifier

Used Random Forest Classifier Algorithm
https://github.com/dilkushsingh/iris-species-classifier

huggingface-spaces numpy pandas python random-forest-classifier scikit-learn streamlit

Last synced: 25 days ago
JSON representation

Used Random Forest Classifier Algorithm

• Host: GitHub
• URL: https://github.com/dilkushsingh/iris-species-classifier
• Owner: dilkushsingh
• License: mit
• Created: 2024-06-21T06:36:29.000Z (7 months ago)
• Default Branch: main
• Last Pushed: 2024-08-24T11:27:31.000Z (5 months ago)
• Last Synced: 2024-11-08T03:39:58.352Z (3 months ago)
• Topics: huggingface-spaces, numpy, pandas, python, random-forest-classifier, scikit-learn, streamlit
• Language: Python
• Homepage: https://iris-species-classifier-ds.streamlit.app/
• Size: 54.7 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# 🌸 Iris Species Classifier

Welcome to the **Iris Species Classifier** project! This repository contains the code for a web application that predicts the species of an Iris flower based on its features. The app uses a Random Forest Classifier to make predictions, providing a reliable and robust model for this classic dataset.

### Deployment

App is live on Streamlit Community [https://iris-species-classifier-ds.streamlit.app/] and Hugging faces [https://huggingface.co/spaces/dilkushsingh/Iris-Species-Classifier]

# Connect with me on LinkedIn [Dilkush Singh](https://linkedin.com/in/dilkushsingh)

## 🧠 Project Overview

The Iris dataset is one of the most famous datasets used in machine learning. It contains 150 samples of iris flowers, each described by four features:

- **Sepal Length**

- **Sepal Width**

- **Petal Length**

- **Petal Width**

The goal of this project is to classify the iris flowers into one of the following species:

- **Setosa**

- **Versicolor**

- **Virginica**

## 🌟 Features

- **User-Friendly Interface:** Easy-to-use web interface built with Streamlit.

##