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

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

Assessing personal growth on LinkedIn with charts. Plot LinkedIn connections over time. Discover what your connections most do and where they most work.

Attempt at reproducing a SGNN's projection layer, but with word n-grams instead of skip-grams. Paper and more: http://aclweb.org/anthology/D18-1105

What about coding a Spiking Neural Network using an automatic differentiation framework? In SNNs, there is a time axis and the neural network sees data throughout time, and activation functions are…

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 diffe…

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

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

[2013] A game for an introductory programming course. I coded a 2D car side scrolling physic engine from scratch.

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.

A lightweight library to do for-loop-styled convolution passes on your iterable objects (e.g.: on a list). Note: this is not a convolution, it is about exposing what would the kernel pass on in the…