Demystifying Machine learning for Industrial IoT

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Machine Learning is a key asset for Industrial IoT scenarios, but is a complex technology that presents many challenges. In this new episode of the IoT Show we will discuss the common Industrial IoT prediction patterns Machine Learning is used to implement and will demo resources and samples made available on GitHub to help you become familiar with Machine Learning for IIoT.

- [0:00](#time=0m00s) Teaser
- [0:30](#time=0m30s) Introductions
- [1:30](#time=1m30s) What are the typical use cases for ML use in IoT solutions?
- [3:30](#time=3m30s) What are the core steps for implementing Machine Learning?
- [7:09](#time=7m09s) Demo: Exploration (problem definition, data acquisition, exploratory analysis)
- [25:00](#time=25m00s) Demo: Experimentation (base line modeling, auto-ML, align Business and ML objectives, Model and data management, training pipeline)
- [35:50](#time=35m50s) Demo: Operation (Business actions mapping, deployment and monitoring)
- [38:12](#time=38m12s) Wrap up and call to action

  1. Microsoft IoT Developers
  2. IoT
  3. Microsoft IoT
  4. Azure IoT
  5. ML
  6. Machine Learning
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