Abirami R., a Data Scientist at Flutura and a budding game changer in the Data Science fraternity, led an interactive webinar on the concept of anomaly detection using machine learning in Industrial IoT.
Key Takeaways post webinar:
- To identify anomalies in any process or data, we first need to identify what is normal or acceptable.
- Extensive EDA and good domain knowledge will help in identifying the anomalies
- Train a machine learning model to learn from the normal behaviour and patterns and simulate the parameters.
- Use the machine learning model to identify anomalies using error.
- Deploy anomaly detection module in batch mode or real time mode.
Hope this webinar added to your knowledge. To attend more such webinars and learn from the recordings, stay updated with the upcoming and trending webinars.
