Forecasting Impact
Forecasting Impact is a bimonthly podcast that aims to disseminate the science and practice of forecasting by introducing prominent academics, practitioners, and visionaries in the forecasting domain. Our vision is to help grow the forecasting community, foster collaboration between academia, industry, and governments, and promote scientific forecasting and good practices.
We will discuss a range of forecasting topics in economics, supply chain, energy, social goods, AI, machine learning, data analytics, education, healthcare, and more.
Forecasting Impact episodes are also available on the IIF YouTube Channel @IIForecasters.
Podcast Team
Chair and Co-host: Dr. Laila Ahadi-Akhlaghi, Senior Technical Advisor at JSI.
Additional co-hosts:
- Dr. Mahdi Abolghasemi, Lecturer in Data Science at The University of Queensland,
- George Boretos, Founder & CEO at FutureUP,
- Dr. Faranak Golestaneh, Data Science Senior Manager at Commonwealth Bank of Australia,
- Mariana Menchero, Senior Forecaster at Nixtla, and
- Arian Sultan Khan, Data Analyst at VAN
Co-hosts in the past have included: Michał Chojnowski, Shari De Baets, Elaine Deschamps, Dr. Sevvandi Kandanaarachchi, Bahman Rostami-Tabar, Anna Sroginis, and Sarah Van der Auweraer.
We welcome your feedback, questions, and suggestions. Please contact us at forecastingimpact@forecasters.org
Forecasting Impact
Eric Siegel on Predictive Analytics Role
Eric Siegel is a leading consultant and former Columbia University professor. He is the founder of the popular Predictive Analytics World and Deep Learning World conference series.
In this episode, Eric shares his decades of experience in predictive analytics. He discusses why ML is useful, and how predictive analytics have been used in business. Eric shares his view on prescriptive analytics, AI, and also explains uplift-modelling concepts, and why it is hard and so powerful.
Eric's Recommendations
Books:
- Competing on Analytics: Updated with a New Introduction, The New Science of Winning by Thomas H. Davenport, Jeanne G. Harris, 2017
- Applied Predictive Analytics: Principles and Techniques for the Professional Data Analyst, by Dean Abbot
- Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die by Eric Siegel
Papers:
- Sculley, David, Gary Holt, Daniel Golovin, Eugene Davydov, Todd Phillips, Dietmar Ebner, Vinay Chaudhary, Michael Young, Jean-Francois Crespo, and Dan Dennison. "Hidden technical debt in machine learning systems." Advances in neural information processing systems 28 (2015).
- Elder IV, John F. "The generalization paradox of ensembles." Journal of Computational and Graphical Statistics 12, no. 4 (2003): 853-864.