Principal Statistician, Procter & Gamble
Machine learning is an important tool when applied to the right problem. The first step – clearly defining the problem – is vitally important any time you are considering data collection or a statistical analysis. For example, is your goal to develop a statistical model for the purpose of explaining, predicting or possibly both? After outlining a simple definition of machine learning and its terminology, this talk will provide a brief introduction to the two general categories of machine learning, supervised learning and unsupervised learning, and show several examples to provide a better understanding of how machine learning is used in industry. It will also cover critical steps to take before building a machine learning model and advanced methods for more complex or unstructured data.