B9DA109 - Machine Learning and Pattern Recognition

Assignment Task

Supervised Machine Learning

Research and choose a suitable dataset and apply linear or logistic regression in Python. Your dataset must have at least 15 variables (including dependent and independent variables)

You should provide a reference of the source of dataset.

Choose dependent and independent variables and apply the algorithm without and with the use of an optimisation algorithm (you have covered stochastic gradient descent algorithm in the class) . Pick the best model that you think is usable in the real-world.

In addition to providing the python code file, you are required to provide critical analysis of your approach and results in a pdf report. Your code and analysis should cover the following points: 

1. Choice of dependent and independent variables and selection of algorithm

2. Data Preparation

3. Feature selection 

4. Model Development and Evaluation 

5. Model Comparison

6. Individual Contribution

Each group member must write individually about their contribution and reflection of learning.

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