KNN Iris Dataset Classification 🌸

This project demonstrates the implementation of the K-Nearest Neighbors (KNN) algorithm to classify flowers in the famous Iris dataset.

📌 Project Overview

The goal of this project is to build a machine learning model that can accurately classify iris flowers into three species:

• Setosa
• Versicolor
• Virginica

The model is trained using the KNN algorithm, which classifies data points based on the majority class among their nearest neighbors.

🛠️ Technologies Used

• Python
• NumPy
• Pandas
• Matplotlib
• Seaborn
• Scikit-learn

📊 Dataset

The Iris dataset is a well-known dataset in machine learning that contains:

• Sepal length
• Sepal width
• Petal length
• Petal width

⚙️ Steps Performed

• Data loading and exploration
• Data preprocessing
• Splitting dataset into training and testing sets
• Applying KNN algorithm
• Model evaluation using accuracy score

🎯 Result

The model successfully classifies the iris species with good accuracy using KNN.