This project demonstrates a simple machine learning workflow using the famous Iris dataset. It covers data preprocessing, model training, evaluation, and prediction using Logistic Regression from scikit-learn.
The project uses the Iris dataset, which contains measurements of iris flowers (sepal length, sepal width, petal length, petal width) to classify them into three species:
- Setosa
- Versicolor
- Virginica
- Load and explore the dataset
- Split features (X) and target labels (y)
- Train a Logistic Regression model
- Evaluate the model’s performance
- Make predictions on new data
Make sure you have the following Python libraries installed:
pip install pandas scikit-learn