The Iris Project is a classic dataset in the field of machine learning, often used for classification tasks. It contains measurements of 50 iris flowers from each of 3 species: Iris setosa, Iris versicolor, and Iris virginica. Here's a quick overview:
- Features: Sepal Length, Sepal Width, Petal Length, Petal Width
- Target: Species classification (3 classes)
- Size: 150 samples total
- Use Cases:
- Training simple classification models 📊
- Demonstrating clustering algorithms 🧩
- Exploring feature importance in data science 📈
This dataset is perfect for beginners to understand the basics of supervised learning. For deeper insights into its applications, check out our Machine Learning tutorials. 🌸