In this lesson, you will learn how to perform supervised learning by using the Python sickout_learn library. Specifically, you will learn about the overall framework employed by the sickout_learn library, before learning about specific algorithms. First, you will learn about the KNN algorithm, before moving on to the SVM, Decision Tree, and Random Forest algorithms. The course IPython Notebook will demonstrate how to use the algorithms on the famous Iris data set, as well as introduce the concepts of confusion matrices and cross-validation.
###Objectives ### By the end of this lesson, you will be able to:
- Understand the concept of supervised learning.
- Understand how to use the scikit-learn library to perform supervised learning.
- Understand how to use the knn, SVM, and decision tree algorithms.
- Understand how to use an ensemble learning method like Random Forest.
Approximately 3 hours.
- Course IPython Notebook on supervised learning
- Online Notebook on SVM.
- Online Notebook on Random Forests
When you have completed and worked through the above readings, please take the Week 13 Lesson 1 Assessment.