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A Multilingual Latent Dirichlet Allocation (LDA) Pipeline with Stop Words Removal, n-gram features, and Inverse Stemming, in Python.
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.
Rough list of my favorite deep learning resources, useful for revisiting topics or for reference. I have got through all of the content listed there, carefully. - Guillaume Chevalier
A lightweight library to do for-loop-styled convolution passes on your iterable objects (e.g.: on a list).
This is code I wrote within less than an hour so as to very roughly draft how I would code a Dynamic RNN Attention Decoder Tree with PyTorch.
Taking a pretrained GloVe model, and using it as a TensorFlow embedding weight layer INSIDE THE GPU. Therefore, you only need to send the INDEX of the words through the GPU data transfer bus, reducing data transfer overhead.
Signal prediction with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier
Custom convolutional neural network on cifar-100 dataset for image classification. Images and their labels are processed to HDF5 data format for use in Caffe.
Human activity recognition example 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) - Guillaume Chevalier
Simple demo of filtering signal with an LP filter and plotting its STFT and Laplace transform, in Python.
Predict whether income exceeds $50K/yr based on census data of the "Adult Dataset". Also known as "Census Income" dataset.
Digit Recognition with scikit-learn's Bernoulli RBM and Logistic Classifier