Machine learning is being used to analyze large amounts of data in a wide variety of industries. While machine learning has many benefits, machine learning is also prone to being attacked. In this session, attendees will be introduced to the idea of adversarial machine learning and attacks to machine learning models. Attendees will learn about some real-world case studies regarding attacks that have impacted top companies in the industry as well as some current open-source industry solutions that aim to increase the security of machine learning algorithms. After the session, attendees will learn about the difference between AI and machine learning and open-source solutions that exist that aim to mitigate adversarial machine learning attacks.