Cardiovascular Predictive Analytics

An in depth approach to predicting the presence of cardiovascular disease through the use of data mining techniques. This area of research is critically important because cardiovascular disease is currently the number one cause of death.

Feel free to check out the on-demand dashboard below (Created in DataStudio From GCP):

https://datastudio.google.com/reporting/f532c9df-d1f1-45bc-910a-1bb85294c1a1/page/lwtqB

In order to run this python notebook:

1. Run: pip install -r requirements.txt
2. Change runtime type to GPU in Google Colab
3. Upload your kaggle.json API key file
4. Run all cells

Machine Learning Models Explored Include:

1. Artificial Neural Networks
2. Decision Trees
3. Naive Bayes Classifiers
4. K-Means Clustering
5. Logistical Regression
6. Linear Regression

Both the Python Jupyter Notebook along with a pure python code file (if needed) are attached

Note: The code will take approximately 23 - 26 minutes to run from start to finish