This course takes a look at modern machine learning techniques. It takes participants through recent advances in supervised and unsupervised methods and algorithms with a focus on complex business applications. Practical implementations include the use of modern recommendation systems packages, XGBoost, CatBoost, LightGBM, transparent inference, SHAP value analysis, mixture of expert architectures and more. It also provides an introduction to deep learning techniques. More specifically, it reviews the use of deep neural networks, deep reinforcement learning, recurrent nets, and convolutional neural networks among others.