The cyber threat landscape today forces organizations to constantly track and correlate millions of external and internal data points across a number of endpoints. It simply is not feasible to manage this volume of information on an ongoing basis with a team of people. Machine learning shines here because it can recognize patterns and predict threats in massive data sets, all at machine speed. By automating the analysis, cyber teams can rapidly detect threats and isolate situations that need deeper human analysis. While machine learning offers tremendous promise for cyber security, it has its share of shortcomings that need to be acknowledged in order to use it appropriately.