Skip to content

Latest commit

 

History

History
17 lines (13 loc) · 1.25 KB

AI.md

File metadata and controls

17 lines (13 loc) · 1.25 KB
Raw

Artificial Intelligence (AI)

  1. LSTMs (Recurrent Neural Networks) for Human Activity Recognition
    Human activity recognition using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six categories (WALKING, WALKING_UPSTAIRS, WALKING_DOWNSTAIRS, SITTING, STANDING, LAYING).
    Project Source: https://github.com/guillaume-chevalier/LSTM-Human-Activity-Recognition

  2. Human activity recognition with stacked residual bidirectional LSTMs
    Human Activity Recognition (HAR) using stacked residual bidirectional-LSTM cells (RNN) with TensorFlow.
    Project Source: https://github.com/guillaume-chevalier/HAR-stacked-residual-bidir-LSTMs

  3. Signal prediction with a seq2seq RNN model in TensorFlow
    Solving different simple toy problems about signal prediction.
    Project Source: https://github.com/guillaume-chevalier/seq2seq-signal-prediction

  4. Hyperopt for solving CIFAR-100 with a convolutional neural network (CNN) built with Keras and TensorFlow, GPU backend
    Auto-optimizing an artificial neural network (and its architecture) on the CIFAR-100 dataset. Could be easily transferred to another dataset or another classification task.
    Project Source: https://github.com/guillaume-chevalier/Hyperopt-Keras-CNN-CIFAR-100