Batch machine learning for predictive maintenance rarely makes good on its promises - ratios of 20 false positives to 1 true positive are common. Correctly integrating the time dimension of your industrial optimization challenge with Datapred will increase accuracy for:
Your time series in the right order, whatever their frequency.
Extract meaningful features in your data, sequentially. Spot and handle outliers automatically.
Hit the ground running with our diverse portfolio of built-in predictive models.
For advanced custom modeling, Datapred is compatible with most open-source machine learning libraries.
Forget selecting the best model: boost performance and versatility by using multiple models at the same time.
Optimize for the right objective, under realistic constraints.
Parallel architecture that optimizes computations at every modeling step.
Pre-built connectors for standard databases, and templates for connecting to non-standard databases and proprietary management systems.
Leverage Datapred’s graph structure to build consistent, flexible and robust machine learning workflows.
Rigorous, online and customizable measurement of your solution’s performance.
Automatic backups at each time step, in your chosen format, for final or intermediate results.
Create a sandbox and continually test the contribution of new data sources and modeling options to your original solution.