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MA5851 Data Science

Question

Answered

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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ICT311 Mobile App Development

Tasks: Assessment and Submission Details Task 1 consists of a code package and a report explaining the design of the app. Submit your code via GitHub or BitBucket, and your report to Blackboard Task 1. Please follow the submission instructions provided in this document. The assignment will be m ...

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The Heap Sort Algorithm

I A REPORT ON THE SORTING ALGORITHMS USED FOR CSE2ALG PROGRAMMING LAB WORK -PART 2 i Abstract This exercise was done to demonstrate how words from text files were read and fed to alexicon then sorted using a heap sort algorithm. The sorted data was then written to another output file together ...

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CSP2108 Introduction to Mobile Applications Development

Task list:• Implement an app using the Corona SDK and Lua that demonstrates the principle of the kNN algorithm. Pre-clustered data has been supplied in CSV format, sourced from Teknomo• Create a three-minute video, demonstrating the functionality of your app• Create a document contain ...

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COMP90056 Stream Computing And Applications

Questions Part 1: Theory questions This Part is worth 1.5 marks. (a) [1.5 marks] Bloom Filter variant. The analysis of the Bloom filter in the slides assumes that the available hash functions are uniform and fully independent. It is known that a hash function with the latter properties requires ...

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