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RUL is the remaining time or cycles that the machine is likely to operate without any failure. By estimating RUL the operator can decide the frequency of scheduled maintenance and avoid unplanned downtime.
In this DataHour, Jidhu will explain the RUL (Remaining Useful Life) estimation of a machine using sensor data using realistic multivariate time-series data for leveraging the power of deep neural networks in the hands-on. He will also focus on how you can build a DCNN (Deep Convolutional Neural Networks) model for the prediction.
Prerequisites: Enthusiasm for learning Data Science and basic knowledge of Deep learning and Time series data.
Jidhu Mohan M
Data Scientist at IBM System Labs
Jidhu Mohan M is currently working as Data Scientist with IBM System Labs.
He has been working as an integral part of corporate research/innovation divisions for more than a decade now with expertise in multi-disciplinary research fields like Industrial AI, Deep Learning, Machine Learning, NLP, KG, Predictive Modeling, Time Series forecasting, Reinforcement Learning, Internet of Things (IoT) and Product Engineering. He has built multiple product MVPs/PoVs which were deployed and have generated new business avenues.
He is a passionate researcher and has filed four patents as part of his research work.
Connect with Jidhu at: https://www.linkedin.com/in/jidhu/
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