🌸 Iris Flower Classification using K-Nearest Neighbors (KNN)

An AI & Machine Learning project that classifies Iris flower species using the K-Nearest Neighbors (KNN) algorithm.
This project demonstrates the complete ML workflow including data preprocessing, model training, evaluation, prediction, and visualization using Python.

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📌 Project Overview

The Iris dataset is one of the most popular beginner-friendly datasets in Machine Learning.
The objective of this project is to predict the species of an Iris flower based on its physical measurements.

Input Features

• Sepal Length
• Sepal Width
• Petal Length
• Petal Width

Predicted Classes

• Iris Setosa
• Iris Versicolor
• Iris Virginica

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🚀 Technologies Used

Technology	Purpose
Python	Programming Language
Pandas	Data Handling
NumPy	Numerical Operations
Matplotlib	Data Visualization
Scikit-learn	Machine Learning Model

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🧠 Machine Learning Algorithm

K-Nearest Neighbors (KNN)

KNN is a supervised Machine Learning algorithm that classifies data points based on the majority class of their nearest neighbors.

KNeighborsClassifier(n_neighbors=3)