Administrative information

Title	Neural Networks
Duration	60
Module	A
Lesson Type	Lecture
Focus	Practical - AI Modelling
Topic	AI - Modelling

Keywords

Neural network,backpropagation,optimization,

Learning Goals

Learners understand the MLP architectre
Learners can construct neural networks with fully connected layers and various activation functions
Learners understand the basic idea of backpropagation and gradient-based methods

Expected Preparation

Learning Events to be Completed Before

Lecture: Model Fitting and Optimization

Obligatory for Students

Review of linear algebra and vector calculus.

Optional for Students

None.

References and background for students:

https://playground.tensorflow.org/

Recommended for Teachers

Familiarize themselves with the demonstration materials.

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 notebooks (shape of the loss function w.r.t. different regularizers, gradient-based optimization algorithms). Give a brief overview of the code.

Outline/time schedule


Duration (min)	Description	Concepts
5	From logistic regression to perceptron	input, weights, bias, sigmoid function
10	Multilayer perceptron and matrix multiplications	input layer, hidden layer, output layer
20	Derivation of the backpropagation scheme	gradient descent, learning rate, backpropagation
10	Activation functions	ReLU, sigmoid, tanh, softmax etc.
10	Loss functions for classification and regression	MSE, binary and categorical cross-entropy
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