The Iris dataset is a classic dataset for classification, machine learning, and data visualization.
The dataset contains: 3 classes (different Iris species) with 50 samples each, and then four numeric properties about those classes: Sepal Length, Sepal Width, Petal Length, and Petal Width.
One species, Iris Setosa, is "linearly separable" from the other two. This means that we can draw a line (or a hyperplane in higher-dimensional spaces) between Iris Setosa samples and samples corresponding to the other two species.
Predicted Attribute: Different Species of Iris plant.
The purpose of this project was to gain introductory exposure to Machine Learning Classification concepts along with data visualization. The project makes heavy use of Scikit-Learn, Pandas and Data Visualization Libraries.
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