15_svms_and_neural_networks

Support vector machines and neural networks

By Gianluca Campanella (g.campanella@estimand.com)

Objectives

By the end of the session, you should be able to:

• Describe the pros and cons of support vector machines
• Define perceptrons and other neural network architectures
• Use scikit-learn and Keras to fit SVMs and neural networks

Plan

The session is designed to be delivered over three hours (including breaks).

Topic	Time
Support vector machines	30 minutes
Support vector machines using scikit-learn	30 minutes
Introduction to neural networks	15 minutes
Neural networks using Keras	30 minutes
Exercises	45 minutes

Materials

• Support vector machines
• Introduction to neural networks
• Support vector machines using scikit-learn
• Neural networks using Keras
• Exercises and solutions