Iris-Flower-Classification-

Problem Statement

The iris flower, scientifically known as Iris, is a distinctive genus of flowering plants. Within this genus, there are three primary species: Iris setosa, Iris versicolor, and Iris virginica. These species exhibit variations in their physical characteristics, particularly in the measurements of their sepal length, sepal width, petal length, and petal width.

Objective:

The objective of this project is to develop a machine learning model capable of learning from the measurements of iris flowers and accurately classifying them into their respective species. The model's primary goal is to automate the classification process based on the distinct characteristics of each iris species.

Project Details:

Iris Species: The dataset consists of iris flowers, specifically from the species setosa, versicolor, and virginica.

Key Measurements: The essential characteristics used for classification include sepal length, sepal width, petal length, and petal width.

Machine Learning Model: The project involves the creation and training of a machine learning model to accurately classify iris flowers based on their measurements.

This project's significance lies in its potential to streamline and automate the classification of iris species, which can have broader applications in botany, horticulture, and environmental monitoring.