Administrative information

Title	Model Fitting and Optimization
Duration	60
Module	A
Lesson Type	Lecture
Focus	Technical - Foundations of AI
Topic	Foundations of AI

Keywords

logistic regression, model fitting, optimization, gradient descent, Newton's method, numerical stability,

Learning Goals

To acquire demonstrable knowledge of what logistic regression is
To acquire demonstrable knowledge of ML inference in non-conjugate models via gradient descent
To acquire demonstrable knowledge on the design and implementation of gradient-based optimization algorithms

Expected Preparation

Learning Events to be Completed Before

Lecture: Inference and Generalisation

Obligatory for Students

Review the basics of Bayesian inference and maximum likelihood
Review elementary vector calculus

Optional for Students

None.

References and background for students:

None.

Recommended for Teachers

Familiarize themselves with the demonstration material

Lesson Materials

The materials of this learning event are available under CC BY-NC-SA 4.0.

Instructions for Teachers

Cover the topics in the lesson outline and demonstrate the concepts using the interactive notebook (relationship between the number of iterations, loss value and decision boundary, show various algorithms and the effect of the learning rate). Give a brief overview of the code.

Outline/time schedule

Duration (min)	Description	Concepts
5	Introduction to linear classification	binary classification, decision boundary
15	Defining a logistic regression model	class-conditional density, sigmoid function, logistic regression
15	Maximum likelihood estimation	binary crossentropy, learning rate, gradient descent
10	Implementation details and numerical stability	numerical stability, overflow
10	Advanced algorithms	Newton's method, line search
5	Demonstration

More information

Click here for an overview of all lesson plans of the master human centred AI

Please visit the home page of the consortium HCAIM

Acknowledgements

The Human-Centered AI Masters programme was co-financed by the Connecting Europe Facility of the European Union Under Grant №CEF-TC-2020-1 Digital Skills 2020-EU-IA-0068.

The materials of this learning event are available under CC BY-NC-SA 4.0

The HCAIM consortium consists of three excellence centres, three SMEs and four Universities