The Iris Flower Classification project aims to build a machine learning model that can accurately predict the species of an iris flower based on its physical characteristics. The project will take in the Iris dataset, which contains measurements of sepal length, sepal width, petal length, and petal width for three different iris species (Setosa, Versicolor, and Virginica). The goal is to train a machine learning model, such as a decision tree or a support vector machine, to learn the relationships between these measurements and the corresponding iris species. Once the model is trained, it can be used to predict the species of a new iris flower based on its measurements.
