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MA5851 Data Science
Task:
Overview
This assignment involves building parts of a prototype NLP solution and investigating the deployment of the NLP solution that could be used by a development team. The initial part of the NLP solution is gathering data using a web scraper. The web scraper collects information from relevant websites and supplements that website data with metadata from additional knowledge databases. Once the data for the NLP solution is gathered, the data need to be processed and cleaned for NLP tasks.
The NLP tasks use the harvested data to solve or investigate a wider NLP issue. Here, you are to apply two NLP tasks, such as Name Entity Recognition, Semantic analysis, Sentiment analysis, etc. The output of one of the NLP tasks may even be one of the inputs to the other NLP task. Once the two NLP tasks and web crawler have been written and documented, these project components need to be made accessible to a wider development team.
To assist a development team integrating your WebCrawler and NLP tasks, you will need to publish your documentation and code in a Git-repository. Additionally, you will provide a highlevel, end-to-end practical data science solution design video presentation
Learning outcomes
1. Apply NLP data science skills, knowledge, and techniques to solve problems in data science NLP projects with a focus on web crawler and content extraction from webpages.
2. Apply NLP tasks in Python
3. Understand how to deploy data science projects into production pipelines
4. Effectively communicate the results of the project as a video
5. Defining of a single issue to be investigated or address using NLP methodologies
6. Sourcing data from webpages and supplementing data from knowledge sources relevant to the issue
7. Developing proto-type NLP tasks that contribute towards addressing the issue
8. Publishing and communicating your contributions to a development team
MA5851 Data Science
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