Deep Learning Approaches to Forecasting and Planning
Wednesday, May 26, 2021
Deep learning models for forecasting and planning have shown significant promise for handling multiple variables, uncovering hidden patterns, and producing accurate forecasts. However, as one might expect, deep learning models are also complex and rife with pitfalls. Since these techniques often seem like a ‘black box,’ managers — both technical and nontechnical backgrounds — can find them hard to master.
In this session, Senior Data Scientist, Javed Ahmed will focus on the intuition behind various deep learning approaches, explore how managers can tackle highly complex models by asking the right questions, and evaluating the models with familiar tools.
Attendees at the Metis session will leave with the tools to:
● Identify types of forecasting applications that can benefit from deep learning
● Broadly understand deep learning approaches relevant to forecasting
● Understand pitfalls related to deep learning approaches, and why simpler models may work better
● Evaluate the results of a forecasting program