Using AWS tools for ML

ML research spans decades and has deep roots in mathematics and statistics. ML algorithms can be used to solve problems in many business applications. In application areas such as advertising, predictive algorithms are used to predict where to discover further new customers based on trends from previous purchasers. Regression algorithms are used to predict stock prices based on prior trends. Services such as Netflix use recommendation algorithms to study the history of a user and enhance the discoverability of new shows that they may be interested in. Artificial Intelligence (AI) applications such as self-driving cars rely heavily on image recognition algorithms that utilize deep learning to effectively discover and label objects on the road. It is important for a data scientist to understand the nuances of different ML algorithms and understand where they should be applied. Using pre-existing libraries helps a data scientist to explore various algorithms for a given application area and evaluate them. AWS offers a large number of libraries that can be used to perform ML tasks, as explained in the ML algorithms and deep learning algorithms parts of this book.