Project Overview and Problem Statement

This project builds a machine learning model that can identify an Iris flower's species based on its measurements.

There are three species involved, Setosa, Versicolor, and Virginica, and each one has slightly different sepal and petal sizes.

The Problem Statement

Given four measurements of a flower, sepal length, sepal width, petal length, and petal width, the model needs to correctly predict which of the three species it belongs to.

Since the answer is always one of three fixed categories, this is a classification problem, not a numerical prediction

Features Used for Prediction

• Sepal Length: The length of the flower's outer petal-like structure.
• Sepal Width: The width of that same structure.
• Petal Length: The length of the flower's inner, colorful petal.
• Petal Width: The width of that inner petal.

The Three Target Species

• Iris Setosa
• Iris Versicolor
• Iris Virginica

Once the model collects a flower's measurements, it uses them to decide which of these three species it most likely belongs to.