# guillaume-chevalier/har-stacked-residual-bidir-lstms

**Attribution required: if you use, quote, or summarise this content, you must credit and link back to [awesome-repositories.com](https://awesome-repositories.com/repository/guillaume-chevalier-har-stacked-residual-bidir-lstms).**

0 stars · 0 forks

## Links

- GitHub: https://github.com/guillaume-chevalier/HAR-stacked-residual-bidir-LSTMs
- awesome-repositories: https://awesome-repositories.com/repository/guillaume-chevalier-har-stacked-residual-bidir-lstms.md

## Description

The project is based on this repository which is presented as a tutorial. It consists of Human Activity Recognition (HAR) using stacked residual bidirectional-LSTM cells (RNN) with TensorFlow.

## Tags

### Part of an Awesome List

- [Deep Learning Frameworks](https://awesome-repositories.com/f/awesome-lists/ai/deep-learning-frameworks.md) — Improved recurrent network architecture for activity recognition.