e-learning

Deep Learning (without Generative Artificial Intelligence) using Python

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Abstract

About This Material

This is a Hands-on Tutorial from the GTN which is usable either for individual self-study, or as a teaching material in a classroom.

Questions this will address

  • to do

Learning Objectives

  • Input data representation
  • Concept of filters
  • Concept of pooling layers
  • Initialising a model with conv layers (code)
  • Concept of RNNs
  • Concept of attention
  • Implementation of RNN (code)
  • Implementation of attention mechanism (code)
  • Implementation of fine-tuning (code)

Licence: Creative Commons Attribution 4.0 International

Keywords: Statistics and machine learning, ai-ml, elixir, jupyter-notebook, work-in-progress

Target audience: Students

Resource type: e-learning

Version: 1

Status: Draft

Prerequisites:

  • Foundational Aspects of Machine Learning
  • Foundational Aspects of Machine Learning using Python
  • Introduction to Galaxy Analyses
  • Introduction to Python
  • Neural networks using Python
  • Python - Warm-up for statistics and machine learning

Learning objectives:

  • Input data representation
  • Concept of filters
  • Concept of pooling layers
  • Initialising a model with conv layers (code)
  • Concept of RNNs
  • Concept of attention
  • Implementation of RNN (code)
  • Implementation of attention mechanism (code)
  • Implementation of fine-tuning (code)

Date modified: 2025-03-11

Date published: 2025-03-11

Authors: Ralf Gabriels

Scientific topics: Statistics and probability

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