In recent years, deep learning has taken the lead in predictive accuracy in many fields of machine learning, and companies are struggling to keep up with the speed of innovation. Arno Candel demonstrates how successful enterprises can augment simple statistical models with more accurate data-driven models to gain a competitive edge. Arno describes how to build smart applications that include data munging, model training and validation, and real-time production deployment--every step is based on open source code (R, Python, Java, Scala, JavaScript, REST) that runs on distributed platforms including Hadoop, Spark, and standard compute clusters. Arno also presents use cases from verticals including insurance, fraud, churn, fintech, and marketing and offers live demos of smart applications on large real-world datasets in distributed clusters.