Administrative information

Title	Batch Processing
Duration	60 min
Module	B
Lesson Type	Lecture
Focus	Technical - Deep Learning
Topic	Batch processing

Keywords

Batch, MiniBatch, Epoch,

Learning Goals

Understand mechanisms behind batch processing and back propagation
Gradient Descent, Batch vs MiniBatch vs Epoch

Expected Preparation

Learning Events to be Completed Before

Obligatory for Students

None.

Optional for Students

None.

References and background for students:

Learning representations by back-propagating errors

Recommended for Teachers

None.

Lesson Materials

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

Instructions for Teachers

See lecture material for information and example class questions.

Outline

Time schedule
Duration (Min)	Description
10	Illustration of Gradient Descent
10	Recap of loss-function
10	Idea of and reasons for Batching
5	Batch Gradient Descent
5	Stochastic Gradient Descent
5	Mini-Batch Gradient Descent
10	Algorithm for one epoch
5	Wrap-up and questions

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