Skip to content
master
Switch branches/tags
Code

Latest commit

 

Git stats

Files

Permalink
Failed to load latest commit information.

Practical 3

Feature Engineering & Model Selection

Overview

In this practical you will learn how to engineer, extract, and select features from different types of data; be introduced to classification models; and perform model selection over parameters of your model. Leading to machine algorithms that can perform well on a wide range of data types.

What is in this Practical Session

  1. Polynomial Features
  2. Model Selection
  3. Classification Models
  4. Image Data
  5. Exercises

It is suggested to read the notebooks in the above order. You can also try the Exercises while you read through the notebooks

Set up your notebook

Open up this repository in binder to get started.

If you have any questions, my email is matthew.higgs@northumbria.ac.uk

About

No description, website, or topics provided.

Resources

Releases

No releases published

Packages

No packages published