Case study: Optimizing energy trading with machine learning

With utilities increasingly focusing on advanced analytics, accurate price forecasting for both wholesale and retail markets brings the promise of moving beyond traditional approaches to offer better pricing, customized experiences to consumers, and optimization of production schedules.

Read this use case to learn how SparkCognition’s automated model building solution, Darwin helps companies improve their bidding strategies, commercial offerings, and production schedules.

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