For this project I created a custom multi-class logistic regression classifier in Python in order to predict employee burnout risk from a work behavioral dataset. I compared the performance between steepest ascent, stochastic gradient ascent, and Newton's method along with different regularizations to see what was the best fit. I then tuned the model’s parameters and compared it with sklearn to come to a conclusion on what was best fit for deployment.