Iris Dataset Classification using Logistic Regression

This project focuses on classifying the Iris dataset using Logistic Regression. It involves data preprocessing, visualization, model training, and evaluation using Python libraries like scikit-learn, pandas, seaborn, and matplotlib. The dataset is split into training and testing sets, and the model’s accuracy is assessed. This project is ideal for those interested in machine learning and data analysis. Future improvements can include hyperparameter tuning and testing other models.