I used Python to predict the loan approval rate for a customer using two different machine learning algorithms. Cleaned the data, checking for null values and imputing by mean. I also converted categorical features to numerical and vice versa, creating dummy variables when necessary. After cleaning the data, I used scikit-learn to implement Random Forest Classifier and Gaussian Naïve Bayes algorithms. Provided the probability whether a customer will be approved or not for each record in the data. Data was provided by State Farm.