Train and test a Python Keras Deep Learning model to categorize different types of Iris.

This data sets consists of 3 different types of irises’ (Setosa, Versicolour, and Virginica) petal and sepal length, stored in a 150x4 numpy.ndarray

You have to import iris dataset like this:

  from sklearn.datasets import load_iris

The dataset is load by this function:

  iris = load_iris()

The model then selects X and y and starts its training with 100 epochs.

After training phase it shows a plot with accuracies and saves the model in local.

This model has a 85/90% accuracy and can categorize different types of Iris.

You are ready to use the model for other images or other training, too! 💥

Iris Dataset