Ecosyste.ms: Awesome

https://github.com/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

activity-recognition deep-learning human-activity-recognition lstm machine-learning neural-network recurrent-neural-networks rnn tensorflow

Last synced: 31 Jul 2024

https://github.com/guillaume-chevalier/seq2seq-signal-prediction

Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier

python seq2seq tensorflow tensorflow-tutorials

Last synced: 31 Jul 2024

https://github.com/guillaume-chevalier/How-to-Grow-Neat-Software-Architecture-out-of-Jupyter-Notebooks

Growing the code out of your notebooks - the right way.

Last synced: 31 Jul 2024

https://github.com/guillaume-chevalier/HAR-stacked-residual-bidir-LSTMs

Using deep stacked residual bidirectional LSTM cells (RNN) with TensorFlow, we do Human Activity Recognition (HAR). Classifying the type of movement amongst 6 categories or 18 categories on 2 different datasets.

bidirectional-lstm-cells human-activity-recognition lstm residual-layers residual-lstm-cells rnn stacked-layers tensorflow

Last synced: 01 Aug 2024

https://github.com/guillaume-chevalier/Linear-Attention-Recurrent-Neural-Network

A recurrent attention module consisting of an LSTM cell which can query its own past cell states by the means of windowed multi-head attention. The formulas are derived from the BN-LSTM and the Transformer Network. The LARNN cell with attention can be easily used inside a loop on the cell state, just like any other RNN. (LARNN)

attention-is-all-you-need attention-mechanism attention-model lstm pytorch recurrent-neural-networks rnn

Last synced: 01 Aug 2024

https://github.com/guillaume-chevalier/ReuBERT

A question-answering chatbot, simply.

Last synced: 01 Aug 2024