Tutorial: Convolutional Neural Networks

Tutorial: Convolutional Neural Networks

Administrative information

Title Convolutional Neural Networks
Duration 60 min
Module B
Lesson Type Tutorial
Focus Technical - Deep Learning
Topic

Deep learning

 

Keywords

CNN,Deep Learning,Python,

 

Learning Goals

  • Implementing and training a CNN for an image classification problem from scratch
  • Fine-tuning of an already trained network
  • Transfer learning using architectures trained on ImageNet

 

Expected Preparation

Learning Events to be Completed Before

Obligatory for Students

  • Theory on CNN

Optional for Students

  • None

References and background for students:

  • None

Recommended for Teachers

None.

 

Lesson Materials

 

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

 

Instructions for Teachers

This Tutorial covers fundamental CNN development, training and testing. Three different tutorial implemented in form of Jupyter Notebook will be shown and discussed. In particular:

  • the implementation of a simple CNN will be shown. The training will be made with a simple freely available dataset (e.g. MNIST). Evaluation in terms of accuracy of a test set after the training stage will be shown.
  • the fine tuning of an already trained network will be made on a new dataset (e.g., Fashion-MNIST). Evaluation and a comparison with a network trained from scratch will be shown and discussed.
  • how to load and save custom models will be shown.

 

Time schedule

 

Duration (min) Description Concepts Activity Material
20 Implementing and training a simple CNN      
20 Fine tuning of an already trained network      
20 load and save architectures    

 

 

 

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

HCAIM Consortium

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    Auteur
    HCAIM Consortium
    Laatst gewijzigd
    2024-05-15 11:20:26
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    Gebruikte Wikiwijs Arrangementen

    HCAIM Consortium. (z.d.).

    Acknowledgement

    https://maken.wikiwijs.nl/198386/Acknowledgement

    HCAIM Consortium. (z.d.).

    Tutorial: Batch processing

    https://maken.wikiwijs.nl/200305/Tutorial__Batch_processing

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