COM6018 Data Science with Python

Week 9 - Curve Fitting with Scikit-Learn

Jon Barker

Overview

• Review of Lab Class 7 (Face Recognition)
• Group Feedback from Assignment 1
• Curve Fitting with Scikit-Learn
• Preview of Lab Class 8 (Predicting CO₂ Atmospheric Concentration)

Review of Lab Class 7

• Building a system for face classification.
• Using the 'Labeled Faces in the Wild' dataset.
• Using Scikit-Learn to evaluate a range of approaches.

The Solution Notebook

The solutions to the lab have been released.

Open the Solution Notebook

Group Feedback from Assignment 1

Group feedback for the Assignment 1 will be presented.

Curve Fitting with Scikit-Learn

This week we will looking at Scikit-Learn to perform regression.

• Using curve fitting as an example.
  • Fitting noisy data with a polynomial function.
  • Fitting periodic data with sine and cosine functions.
• Estimating parameters using linear regression.

Curve Fitting with Scikit-Learn Tutorial

Link to the Curve Fitting with Scikit-Learn tutorial

Lab Class 7 Preview

We will use Scikit-Learn to fit the CO₂ atmospheric concentration data.

We will then use our fitting model to predict future CO₂ atmospheric concentration.

On what date will the CO₂ atmospheric concentration reach 450 ppm?

Lab Class 7 Preview

Link to lab class

Next Steps

• Complete/Review Lab Class 7:

  • Complete the Face Recognition lab.
  • We will be using this data in Assignment 2 (released next Monday)

• Prepare for Lab Class 8:

  • Read through the Curve Fitting with Scikit-Learn tutorial.

• Marks and some Individual Feedback for Assignment 1 will be released on Friday