Dataset link

Select a real-world classification problem
Select a suitable dataset for the chosen problem (must have 1200 samples after pre-processing)
Select more than one approriate ML algo
Evaluate the created models on the selected data
Tune the models to achieve better performace

5 min demo video, with execution of all stages and output
Demo must describe what is happening and give clearn reasoning
Ensure proper visibility of the Text, Table, Graphs, reasonable font size, no noise, not blurry.
Must use Jupyter Notebook

Analysing and pre-processing the data
Applying different algorithms and methods to build learning models
Making appropriate adjustments to improve the models’ performances
Evaluating the models (metrics, cross validation, confusion matrices, etc.)
Comparing the approaches and results of other existing pieces of work on the same problem

Report:

Notes:

Your reports should focus on how algorithms/methods/techniques are actually applied or developments that are novel and specific to your work rather than how they work theoretically
Your report should include appropriate outcomes such as data analysis diagrams, outcomes from the models, code snippets, etc. to support your text.
Include all your source code as text in Appendix B at the end of the report. Do not use screenshots of your code in Appendix B Your code muse be presented as text (see coursework template).
A course work template is provided as a guide in “Assessment” section on Aula
The 2000-word limit is the absolute maximum word count for the whole report. Reports that are more than 10% over the word limit will result in a reduction of 10% of the marks e.g., a mark of 60% will be reduced by 6% to 54%. The word limit includes quotations, but excludes the (GitHub, datasets, OneDrive) URLs, bibliography, reference list, and appendices (see coursework template)

singhh48/9753941-HS-s1