Iris Classification

Description

Table of Contents

• General Information
• Technologies Used
• Features
• Dataset
• Setup
• Project requirements/dependencies
• Extentions for Vscode
• Acknowledgements
• Contact

General Information:

• Iris class : setosa;versicolor;virginica
• The proposed model classifies the iris flower with the input data.
• I have used SVM model for the classification using sklearn.svm

Technologies Used:

• VScode, pandas, seaborn, numppy, matplotlib, pickle and sklearn

Features:

1. Classifies the species of iris flower instantly.

Dataset:

• https://archive.ics.uci.edu/dataset/53/iris

Setup:-

Project requirements/dependencies:

• Python version 3.9.6

• Visual Studio Code version 1.60.2

Extentions for Vscode:

• Python

Just download the files or clone the project in your device and install the dependencies and we are good to go.

How to access the application:

Directly run the iris_classification.ipynb file in VSCode(Python 3.9 64 bit)

Give the input data to predict the value to the model

Acknowledgements

https://archive.ics.uci.edu/dataset/53/iris

DataFlair

Contact

Created by R JOEL SHARON