By utilizing pandas and various datasets about the living conditions in different cities, we are able to determine the optimal city for the user to live in based on their preferences.
This project is a spatio-temporal analysis that helps identifying the high-risk areas and contributing factors to HF to gain more insights into the HF hospitalization problems in Texas.
A program where people can select locations they are interested in, factors they would like to consider and gain higher points (percentages) when the location and their interests align
Applies reinforcement learning to make the best out of stock market
Understanding the correlation of climate anomalies using MATLAB spatio-temporal regression
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