Assignment Task :
Overview
This is a revised project specification for the 2020 delivery of the Deep Learning class. The revised project specification has been developed in light of the Covid-19 situation. This project specification differs from the original outline I gave verbally in our last physical class on the 10th of March. For example, there was an original plan to have a two stage submission; this has been dropped to simplify the process.
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Get Help Now!The goal of the project is to perform a systematic investigation of a number of Deep Learning methods in the context of text processing tasks and benchmark these methods against classical methods where appropriate.
This project has been designed to give you a range of task elements that you can use to build up your skills in Deep Learning. As such this project specification is detailed and descriptive.
The outputs for this project will be a detailed report (minimum 11 pages formatted as per this document), source code, and a trained model. Detail on what is to be included in each of these pieces is detailed below. The report is to be submitted via Brightspace with links to a code archive (.zip or .tar.gz), and a link to two trained models (described below).
Your implementation should be made in Keras / TensorFlow and you cannot use any alternative data set.
Task Specification
Part 1: IMDB Modelling
The core of this project is based around a simple task — performing sentiment analysis with the IMDB dataset given here:
There are 50,000 documents in the IMDB corpus. Split these into the following ratio for analysis:
- Train: 50%
- Validation: 30%
- Test: 20%
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