Webinar: How to build more meaningful machine learning models with third-party data
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You will learn how:
Third-party data can enrich your first-party data
AWS services such as Amazon SageMaker and Amazon QuickSight can make building ML models easier and more accurate
PredictHQ's demand intelligence can help improve forecasting accuracy
Delivery company, Favor, improved its mean absolute percentage error (MAPE) with PredictHQ data and Amazon SageMaker
You can find, discover, and use third-party data and APIs from AWS Data Exchange.
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Featured Speakers
Stephanie BouicLead Customer Success Manager
Kevin JohnsonHead of Data Science, Favor
Demand Forecasting: Incorporating events into models for smarter forecasting.
Customer Stories
Labor optimization: Ensuring the right number of drivers and store staff to meet demand.
Customer stories
PredictHQ has supplemented incomplete data sets, including unticketed events and cancelled events, to power pricing strategies and operational decisions.
Customer Stories
Demand forecasting: Incorporating events into their Antuit-built models to better understand demand across 9600 stores.
Customer Stories
Amazon Alexa's "Events Near Me" feature uses PredictHQ data to inform users about local events.
Blog
Demand forecasting: Getting drivers in the right place ahead of time to improve pick-up times.
Customer stories
Event visibility: Available in Zartico’s platform enabling deeper insight and smarter decisions.
Customer Stories
Pricing: A key source of intelligence for the OTA Insights platform, enabling smarter pricing.
Customer Stories
Labor optimization: Enriching the Legion Technologies platform, used by retailers to reduce labor inefficiencies.
Customer Stories
