LSTM-Human-Activity-Recognition

Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier

neural-network machine-learning tensorflow deep-learning

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Jupyter Notebook Language

mit License

100 SrcLog Score

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$9.0K

Market Value

$28.0K

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12 data points · 2021-08-01 → 2026-04-01

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What is the guillaume-chevalier/LSTM-Human-Activity-Recognition GitHub project? Description: "Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier". Written in Jupyter Notebook. Explain what it does, its main use cases, key features, and who would benefit from using it.

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