This project is about data collected in the healthcare regarding heart attacks in men and women. The dataset has 303 entries or observations and 14 columns. It doesn’t contain missing values. Minimal data wrangling was done. The target variable encompasses 0 and 1. 0 for normal individual and 1 for an individual having the disease. The data was split into train and test set. Logistic regression is selected to train the model. Then the test set was used to validate the model. We note an accuracy of 85% of the model. The Jupyter notebook is extensively documented. Thus, give an idea of what code does what. For further work, since the healthcare system is a sensitive domain, we recommend using an ensemble model or even neural network to get a better hypothesis that represents the data which will, consequently, increase the accuracy of the model.
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