Michael Grogan

Michael Grogan is a data scientist with expertise in TensorFlow and time series analysis. His educational background is a master’s degree in economics from University College Cork, Ireland. As such, much of his work has been in the domain of business intelligence; i.e. using machine learning technologies to develop solutions to a wide range of business problems. He has implemented time series solutions for organizations across a range of industries through implementation of statistical analysis as well as more advanced machine learning methodologies. In addition, he has delivered numerous seminars and training courses in the areas of data science and machine learning, including for Manning and O'Reilly Media.

projects by Michael Grogan

Time Series Forecasting with Bayesian Modeling

5 weeks · 4-6 hours per week average · ADVANCED

Included with a Manning Online subscription

catalog / Data Science

Bayesian-based probability and time series methods allow data scientists to adapt their models to uncertainty and better predict outcomes. In this series of liveProjects, you’ll take on the role of a data scientist making customer predictions for hotels and airlines. You’ll use ARIMA, Bayesian dynamic linear modeling, PyMC3 and TensorFlow Probability to model hotel booking cancelations, and implement a Prophet model with uncertainty analysis to forecast air passenger numbers. Each project in the series is focused on a different time series forecasting model, allowing you to compare model performance and choose the skills most relevant to your career development.