e-learning

Deep Learning (Part 1) - Feedforward neural networks (FNN)

Abstract

Artificial neural networks are a machine learning discipline roughly inspired by how neurons in a

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

  • What is a feedforward neural network (FNN)?
  • What are some applications of FNN?

Learning Objectives

  • Understand the inspiration for neural networks
  • Learn various activation functions, and classification/regression problems solved by neural networks
  • Discuss various cost/loss functions and the backpropagation algorithm
  • Learn how to create a neural network using Galaxy's deep learning tools
  • Solve a simple regression problem, car purchase price prediction, via FNN in Galaxy

Licence: Creative Commons Attribution 4.0 International

Keywords: Statistics and machine learning

Target audience: Students

Resource type: e-learning

Version: 12

Status: Active

Prerequisites:

  • Introduction to Galaxy Analyses
  • Introduction to deep learning

Learning objectives:

  • Understand the inspiration for neural networks
  • Learn various activation functions, and classification/regression problems solved by neural networks
  • Discuss various cost/loss functions and the backpropagation algorithm
  • Learn how to create a neural network using Galaxy's deep learning tools
  • Solve a simple regression problem, car purchase price prediction, via FNN in Galaxy

Date modified: 2024-06-14

Date published: 2021-04-28

Authors: Kaivan Kamali

Contributors: Kaivan Kamali

Scientific topics: Statistics and probability


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