Deep Learning on Microcontrollers: Learn how to develop embedded AI applications using TinyML by Atul Krishna Gupta & Dr. Siva Prasad Nandyala

Author:Atul Krishna Gupta & Dr. Siva Prasad Nandyala [Gupta, Atul Krishna & Nandyala, Dr. Siva Prasad]
Language: eng
Format: epub
ISBN: 9789355518002
Publisher: BPB Publications
Published: 2023-06-15T00:00:00+00:00

Collect and label a dataset: First, you need to collect and label a dataset to train your ML model on. This can be done using the Edge Impulse Studio, which allows you to collect data from sensors and label it for training.

Train a ML model: Next, you can use the Edge Impulse Studio to train a machine learning model on your dataset. The platform provides a range of pre-built machine learning models that you can use, or you can build your own custom model using TensorFlow or Keras.

Optimize and compress the model: Once you have trained a machine learning model, you can use the Edge Impulse Studio to optimize and compress the model for deployment on your edge device. This can be done using techniques such as quantization and pruning, which reduce the model size and complexity without significantly impacting performance.

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