A classic machine learning project that trains a Logistic Regression model to classify the species of Iris flowers based on their sepal and petal measurements.
This project demonstrates a complete, beginner-friendly machine learning workflow:
- Data Loading: Using the built-in Iris dataset from scikit-learn.
- Data Visualization: Using seaborn's pairplot to explore relationships between features.
- Model Training: Implementing a Logistic Regression classifier.
- Model Evaluation: Checking the model's performance with an accuracy report and a confusion matrix.
- Python
- scikit-learn
- pandas
- seaborn
- Matplotlib
- Jupyter Notebook