e-learning
Deep Learning (Part 2) - Recurrent neural networks (RNN)
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
Scientific topics: Statistics and probability
External resources:
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