Decision Boundary for a Series of Machine Learning Models

I train a series of Machine Learning models using the iris dataset, construct synthetic data from the extreme points within the data and test a number of Machine Learning models in order to draw the decision boundaries from which the models make predictions in a 2D space, which is useful for illustrative purposes and understanding on how different Machine Learning models make predictions.

Time Series Classification Synthetic vs Real Financial Time Series

I analyse the difference between two time series and obtain a 67% accuracy (on anonymous data)

Series of Hackerrank Competitions

I show my solutions to a few Hackerrank competitions/problems I had completed and discuss the models and solutions.