Machine Learning project with the goal of creating a model that can predict Heart Disease on patients thanks to the dataset provided by UCI Machine Learning Repository: https://archive.ics.uci.edu/ml/datasets/heart+disease
We will be doing building our model through a Jupyter Notebook contained in the Classification.ipynb file so we can test at the moment every manipulation or visualization of the data.
To do this we will be using these technologies:
- Pandas
- NumPy
- SciKit-Learn
- Matplotlib
- Python
- Jupyter Notebook
Also, this is a problem of classification since each patient will be tagged as "1" (heart disease) or "0" (no heart disease).
The main goal of this project is to accomplish a 95% of accuracy so we can say that we have a very robust model. To make this we will evaluating the model, improving it and testing it in different scenarios.