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
Classify human movements into categories like walking or sitting using smartphone sensor data and LSTM models.
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Free · no card · unsubscribe anytimeHuman Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier
LSTM-Human-Activity-Recognition has 3.5k stars on GitHub. It has been forked 936 times. LSTM-Human-Activity-Recognition is written mainly in Jupyter Notebook. It has been in active development since 2016. LSTM-Human-Activity-Recognition is available under the MIT license. Its main topics are activity-recognition, deep-learning, human-activity-recognition, lstm.
What is 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
Is LSTM-Human-Activity-Recognition open source?
LSTM-Human-Activity-Recognition is an open-source project. It is released under the MIT license.
Is LSTM-Human-Activity-Recognition free?
Yes. LSTM-Human-Activity-Recognition is free and open source — you can use, modify and self-host it.
What license does LSTM-Human-Activity-Recognition use?
LSTM-Human-Activity-Recognition is available under the MIT license.
What language is LSTM-Human-Activity-Recognition written in?
LSTM-Human-Activity-Recognition is written mainly in Jupyter Notebook.
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