e-learning

Deep Learning (Part 2) - Recurrent neural networks (RNN)

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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 recurrent neural network (RNN)?
  • What are some applications of RNN?

Learning Objectives

  • Understand the difference between feedforward neural networks (FNN) and RNN
  • Learn various RNN types and architectures
  • Learn how to create a neural network using Galaxy's deep learning tools
  • Solve a sentiment analysis problem on IMDB movie review dataset using RNN in Galaxy

Licence: Creative Commons Attribution 4.0 International

Keywords: Statistics and machine learning

Target audience: Students

Resource type: e-learning

Version: 14

Status: Active

Prerequisites:

  • Deep Learning (Part 1) - Feedforward neural networks (FNN)
  • Feedforward neural networks (FNN) Deep Learning - Part 1
  • Introduction to Galaxy Analyses
  • Introduction to deep learning

Learning objectives:

  • Understand the difference between feedforward neural networks (FNN) and RNN
  • Learn various RNN types and architectures
  • Learn how to create a neural network using Galaxy's deep learning tools
  • Solve a sentiment analysis problem on IMDB movie review dataset using RNN in Galaxy

Date modified: 2024-06-14

Date published: 2021-02-23

Authors: Kaivan Kamali

Contributors: Kaivan Kamali

Scientific topics: Statistics and probability

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