Next-generation time series: Forecasting for the real world, not the ideal world
Solve time series problems with AI
whitepaper
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Time series models make forecasts by learning from history, using data that ranges from individual transactions to data collected daily, weekly, or over a longer term. But turning that data into accurate predictions can be a very complicated process, involving a balance between finding the best data sources and creating the best features from them. It also means incorporating a deep understanding of your business.
Knowing how to approach time series projects is crucial for organisations in their quest to become AI-driven. This eBook looks at the many ways organisations are tackling some of the most valuable, yet difficult, time series problems.
Download this eBook to learn about:
- The current state of time series analysis
- Specific time series applications, such as demand forecasting and anomaly detection
- How to choose the right time series use cases
- How DataRobot’s enterprise AI platform solves time series problems
