Transforming Industrial IoT with Cognitive Anomaly Detection and Prediction

On-demand Webinar

Today, predictive maintenance and the industrial Internet of Things (IoT) have become the number one investment priority for executives at asset-intensive companies. Despite this, a clear majority of organizations are struggling to reap actual benefits from these investments.

To learn more, watch our recent webinar, “Transforming Industrial IoT with Cognitive Anomaly Detection and Prediction.” In this session, Dr. Kirk D Borne, Chief Data Scientist at Booz Allen Hamilton, and Taj Darra, Data Scientist at Progress DataRPM, discuss the various applications of machine learning and predictive maintenance across different industries.

Webinar topics include:

  • Digital transformation for the connected enterprise
  • The state of predictive maintenance
  • Using machine learning for surprise discovery, prediction and prescriptive analytics
  • An overview of anomaly detection: local vs. global, point anomalies vs. gradual divergence from normal, magnitude based vs. contextual
  • Application of supervised and unsupervised learning for time-series data
  • Live use case demonstration


Dr. Kirk D. Borne

Dr. Kirk D. Borne

Chief Data Scientist
Booz Allen Hamilton

Taj Darra

Taj Darra

Data Scientist
Progress DataRPM

About DataRPM

DataRPM is an award-winning predictive analytics company focused on delivering the next generation predictive maintenance solutions for the Industrial IoT. DataRPM platform automates data science leveraging the next frontier in machine learning known as meta-learning, which is machine learning on machine learning. The platform increases prediction quality and accuracy by over 300% in 1/30th the time and resources delivering 30% in cost savings or revenue growth for business problems around predicting asset failures, reducing maintenance costs, optimizing inventory and resources, predicting quality issues, forecasting warranty and insurance claims and managing risks better.

Industry Recognitions and Awards

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