Machine Learning Lifecycle 2021 Conference
Cognilytica’s Machine Learning Lifecycle Virtual Conference is a three day online experience January 26-28, 2021 focused on the machine learning lifecycle including ML Operations, building models, and model management!
Machine Learning Lifecycle 2021 Conference
Using AI and Time Series Models to Improve Demand Forecasting
On Demand
Presented by:
DataRobot

DataRobot is the leader in enterprise AI, delivering trusted AI technology and ROI enablement services to global enterprises. DataRobot’s enterprise AI platform democratizes data science with end-to-end automation for building, deploying, and managing machine learning models.

About this Session

Time series machine learning models allow organizations to predict future values based on past and present data. Translation: companies can use time series to solve critical problems such as optimizing staffing levels, managing inventory, forecasting future product demand, and more.

In this on-demand session, DataRobot’s Chief Scientist Michael Schmidt and General Manager of Time Series Jay Schuren explain time series analysis and its real-world use cases with a focus on retail demand forecasting methods. The webinar concludes with a demo of DataRobot Time Series, which makes it possible for organizations to automatically develop highly accurate time series models without programming knowledge.

You’ll discover:

  • Why time series analysis is critical to any organization dealing with time-sensitive operations
  • Key challenges companies face when looking to develop traditional time series machine learning models
  • Time series use cases and success stories
  • A demo of DataRobot Time Series showcasing how the product automates time series feature engineering, problem setup, backtesting, and modeling to achieve the highest possible accuracy
Featured Presenters
Supported By

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