This project is a demonstration of classifying Iris flowers using machine learning techniques. The Iris flower dataset is a popular dataset in the field of machine learning and is often used for introductory examples. The project aims to predict the species of an Iris flower based on four features: sepal length, sepal width, petal length, and petal width. The dataset contains 150 instances with three different species: setosa, versicolor, and virginica. #Dataset The dataset used in this project is the Iris flower dataset, which is widely available in machine learning libraries and repositories. The dataset consists of 150 samples, where each sample has four features (sepal length, sepal width, petal length, and petal width) and a corresponding label indicating the species of the Iris flower