Discuss the results using appropriate methods as discussed in the module.

Assignment:
apply modern machine learning techniques to solve real-world analytics problems. submit a comprehensive report detailing the proposed work, results and conclusions
The report will be submitted as one deliverable in the form of a written report. The standard of academic writing should be excellent. (Maximum words: 4000 words, excluding tables, figures and references).

Assignment descriiption:
Use modern machine learning techniques and tools to identify, analyse and solve a domain-specific problem. It will you to have the required technical expertise that are required by data scientists to construct and evaluate the effectiveness of AI systems.

Descriiption:
The assessment is in the form of an individual report. You have to follow the below steps in order to complete the assessment successfully:
1. select a domain of interest (e.g. Healthcare, Education, Sport, Finance, Meteorology, etc.)
2. find a data set that is related to the chosen domain. The chosen data set should be publicly available (eg, Kaggle, UCI repository, etc.) with 1,000 rows/instances and 5 columns/attributes (at least).
3. identify three different machine learning problems (where at least one will be supervised & at least one will be unsupervised) that are related to the dataset.
4. critically evaluate the chosen machine learning problems and propose solutions for them using supervised and unsupervised techniques. The solution should include data prepressing, data exploration, model building and model evaluation.
5. Discuss the results using appropriate methods as discussed in the module.

Additional details:
• submit a report of max 4,000 words (excluding code, tables, references and figures) in DOCX/PDF format.
• Ideally, the reports should include the following sections:
Cover page (report title)
o Domain descriiption.
o Problems definition.
o Data set descriiption.
o Data set exploration (preprocessing and wrangling).
o Experiments (three machine learning techniques) and evaluations. o Analysis and Results.
o Conclusions.
o References.
o Appendixes: (codes, charts, etc.)
Additional information:
• References (as per Harvard Referencing Style)
• Report format for the submissions is DOCX.

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