guillaume-chevalier / 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

Date Created 2016-05-18 (8 years ago)
Commits 29 (last one 2 years ago)
Stargazers 3,376 (0 this week)
Watchers 161 (0 this week)
Forks 940
License mit
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RepositoryStats indexes 618,350 repositories, of these guillaume-chevalier/LSTM-Human-Activity-Recognition is ranked #15,209 (98th percentile) for total stargazers, and #9,562 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #364/18,432.

guillaume-chevalier/LSTM-Human-Activity-Recognition is also tagged with popular topics, for these it's ranked: deep-learning (#481/8711),  machine-learning (#505/8271),  tensorflow (#158/2286),  neural-network (#87/1123)

Other Information

guillaume-chevalier/LSTM-Human-Activity-Recognition has 2 open pull requests on Github, 1 pull request has been merged over the lifetime of the repository.

Github issues are enabled, there are 20 open issues and 21 closed issues.

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Recent Commit History

1 commits on the default branch (master) since jan '22

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updated: 2025-02-19 @ 10:54am, id: 59073471 / R_kgDOA4Vjvw