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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... Iris dataset: http://archive.ics.uci.edu/ml/dataset... Nearest Neighbors user guide: http://scikit-learn.org/stable/module... KNeighborsClassifier class documentation: http://scikit-learn.org/stable/module... Logistic Regression user guide: http://scikit-learn.org/stable/module... LogisticRegression class documentation: http://scikit-learn.org/stable/module... Videos from An Introduction to Statistical Learning: https://www.dataschool.io/15-hours-of... WANT TO GET BETTER AT MACHINE LEARNING? HERE ARE YOUR NEXT STEPS: 1) WATCH my scikit-learn video series: • Machine learning in Python with sciki... 2) SUBSCRIBE for more videos: https://www.youtube.com/dataschool?su... 3) JOIN "Data School Insiders" to access bonus content: / dataschool 4) ENROLL in my Machine Learning course: https://www.dataschool.io/learn/ 5) LET'S CONNECT! - Newsletter: https://www.dataschool.io/subscribe/ - Twitter: / justmarkham - Facebook: / datascienceschool - LinkedIn: / justmarkham