Supervised Learning

Overview

What you'll learn

• Understand how the K-Nearest Neighbor algorithm works and how to code it in Python
• Understand how the Support Vector Machine algorithm works and how to code it in Python
• Understand how different types of Regression algorithm work and how to code them in Python
• Understand how the Random Forest algorithm works and how to code it in Python
• Understand how the Decision Trees algorithm works and how to code it in Python
• Evaluate different supervised learning algorithms for a given problem

Skills you'll practise

K-Nearest Neighbors AlgorithmRandom Forest AlgorithmScikit-Learn (Python Package)Supervised LearningSupport Vector Machines (SVM)Decision Tree LearningPython (Programming Language)AlgorithmsTop Secret-Sensitive Compartmented Information (TS/SCI Clearance)

Advantages and disadvantages

Some points apply to every course of this kind; see how we rank.

Before you start

Students should have a basic level of coding knowledge in Python.

Taught by

• Michael Scott BrownProgram Chair of the Software Engineering Master’s