Pinned Repositories
Awesome-Deep-Learning-Resources
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
GloVe-as-a-TensorFlow-Embedding-Layer
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.
HAR-stacked-residual-bidir-LSTMs
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 different datasets.
How-to-Grow-Neat-Software-Architecture-out-of-Jupyter-Notebooks
Growing the code out of your notebooks - the right way.
Hyperopt-Keras-CNN-CIFAR-100
Auto-optimizing a neural net (and its architecture) on the CIFAR-100 dataset. Could be easily transferred to another dataset or another classification task.
Linear-Attention-Recurrent-Neural-Network
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. (LARNN)
LSTM-Human-Activity-Recognition
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
seq2seq-signal-prediction
Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier
Spiking-Neural-Network-SNN-with-PyTorch-where-Backpropagation-engenders-STDP
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 instead spikes that are raised past a certain pre-activation threshold. Pre-activation values constantly fades if neurons aren't excited enough.
Neuraxle
The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.
guillaume-chevalier's Repositories
guillaume-chevalier/LSTM-Human-Activity-Recognition
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
guillaume-chevalier/Awesome-Deep-Learning-Resources
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
guillaume-chevalier/seq2seq-signal-prediction
Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier
guillaume-chevalier/How-to-Grow-Neat-Software-Architecture-out-of-Jupyter-Notebooks
Growing the code out of your notebooks - the right way.
guillaume-chevalier/HAR-stacked-residual-bidir-LSTMs
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 different datasets.
guillaume-chevalier/Spiking-Neural-Network-SNN-with-PyTorch-where-Backpropagation-engenders-STDP
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 instead spikes that are raised past a certain pre-activation threshold. Pre-activation values constantly fades if neurons aren't excited enough.
guillaume-chevalier/PyTorch-Dynamic-RNN-Attention-Decoder-Tree
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.
guillaume-chevalier/LinkedIn-Connections-Growth-Analysis
Assessing personal growth on LinkedIn with charts. Plot LinkedIn connections over time. Discover what your connections most do and where they most work.
guillaume-chevalier/SGNN-Self-Governing-Neural-Networks-Projection-Layer
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
guillaume-chevalier/EDA-for-Cybersecurity-Intrusion-Detection-KDD-Cup-99
guillaume-chevalier/awesome-python
A curated list of awesome Python frameworks, libraries, software and resources
guillaume-chevalier/python-conv-lib
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 first place in your loops.
guillaume-chevalier/awesome-deep-learning
A curated list of awesome Deep Learning tutorials, projects and communities.
guillaume-chevalier/awesome-jupyter
A curated list of awesome Jupyter projects, libraries and resources
guillaume-chevalier/awesome-analytics
A curated list of analytics frameworks, software and other tools.
guillaume-chevalier/dotfiles
guillaume-chevalier/guillaume-chevalier
guillaume-chevalier/Multi-Layer-Perceptron
guillaume-chevalier/Neuraxle
Code Machine Learning Pipelines - The Right Way.
guillaume-chevalier/scikit-learn
scikit-learn: machine learning in Python
guillaume-chevalier/seq2seq-attention
Attention mechanism for time series using tensorflow 2
guillaume-chevalier/ansible-examples
A few starter examples of ansible playbooks, to show features and how they work together. See http://galaxy.ansible.com for example roles from the Ansible community for deploying many popular applications.
guillaume-chevalier/awesome-seml
A curated list of articles that cover the software engineering best practices for building machine learning applications.
guillaume-chevalier/sphinx-gallery
Sphinx extension for automatic generation of an example gallery
guillaume-chevalier/blog
guillaume-chevalier/datascience-wiki
Wiki for /r/datascience
guillaume-chevalier/Machine-Learning-Figures
guillaume-chevalier/medium
guillaume-chevalier/NanoBot
[2013] A game for an introductory programming course. I coded a 2D car side scrolling physic engine from scratch.
guillaume-chevalier/staged-recipes
A place to submit conda recipes before they become fully fledged conda-forge feedstocks