# guillaume-chevalier/LSTM-Human-Activity-Recognition

<https://repo.masters-masters.com/en/repos/guillaume-chevalier/LSTM-Human-Activity-Recognition>

[Home](https://repo.masters-masters.com/en) › [guillaume-chevalier](https://repo.masters-masters.com/en/owners/guillaume-chevalier) › [LSTM-Human-Activity-Recognition](https://repo.masters-masters.com/en/repos/guillaume-chevalier/LSTM-Human-Activity-Recognition)

guillaume-chevalier/LSTM-Human-Activity-Recognition has 3,490 stars on GitHub. Its RepoMasters card: RC tier. Human Activity Recognition example using…

| Field | Value |
| --- | --- |
| Owner | [guillaume-chevalier](https://repo.masters-masters.com/en/owners/guillaume-chevalier) |
| Stars | 3,490 |
| Forks | 928 |
| Language | [Jupyter Notebook](https://repo.masters-masters.com/en/languages/jupyter-notebook) |
| License | MIT |
| Created | 2016 |
| Topics | machine-learning, deep-learning, lstm, human-activity-recognition, neural-network, rnn, recurrent-neural-networks, tensorflow, activity-recognition |
| Tier | [RC (2,000 to 4,999 ★)](https://repo.masters-masters.com/en/ranks/blockbuster) |
| View on GitHub | [guillaume-chevalier/LSTM-Human-Activity-Recognition](https://github.com/guillaume-chevalier/LSTM-Human-Activity-Recognition) |

## Repository

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

The tier for repos with 2,000 to 4,999 ★. Published odds per card pulled: 3%. Rarity: Epic.

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