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The article lists 7 steps to build a smart home AI training dataset:

  • Identify the scope of the project and the data required.
  • Collect data from different sources.
  • Where to look for data.
  • Identify sources from where data could be collected, i.e., Sensors, Camera Microphone.
  • Split the data into training, validation, and test sets.
  • Train the AI model using the dataset.
  • Evaluate the model and make improvements as needed.

The article also stresses the importance of a diverse and representative dataset to create an AI model that can generalize well to new situations and devices. It also highlights that creating a smart home AI training dataset requires a combination of technical expertise and domain knowledge. The article is useful for those looking to build a smart home AI system and provides a step-by-step guide on creating a training dataset for the same.

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