IRIS SPECEIS CLASSIFIER

This Python project aims to classify the species of Iris flowers based on the measurements of petal and sepal lengths and breadths using machine learning techniques. The Iris dataset, which is commonly used in machine learning applications, will be utilized for this project. The project will involve data preprocessing, feature engineering, and model building using various classification algorithms such as logistic regression, decision trees, random forests, and support vector machines. The performance of these models will be evaluated using accuracy, precision, recall, F1-score, and confusion matrix. The outcome of this project will be a Python application that can predict the species of an Iris flower given its petal and sepal measurements with high accuracy. This application can be used in various fields, such as agriculture and botany, to quickly identify the species of Iris flowers without the need for manual identification.