Now that we're familiar with the famous iris dataset, let's actually use a classification model in scikit-learn to predict the species of an iris! We'll learn how the K-nearest neighbors (KNN) model works, and then walk through the four steps for model training and prediction in scikit-learn. Finally, we'll see how easy it is to try out a different classification model, namely logistic regression.

Download the notebook: https://github.com/justmarkham/scikit-learn-videos
Iris dataset: http://archive.ics.uci.edu/ml/datasets/Iris
Nearest Neighbors user guide: http://scikit-learn.org/stable/modules/neighbors.html
KNeighborsClassifier class documentation: http://scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsClassifier.html
Logistic Regression user guide: http://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
LogisticRegression class documentation: http://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html
Videos from An Introduction to Statistical Learning: https://www.dataschool.io/15-hours-of-expert-machine-learning-videos/

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