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www.neuraxle.org
PublicNeuraxle
PublicThe 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 enviro…dotfiles
Publicstaged-recipes
PublicNew-Empty-Python-Project-Base
Public templateThe Perfect Python Project Template. Bored of coding anew the same thing for your new Python projects? Here is what you need. Click below on the "use this template" green button to start using it instantly. Rename the "project" folder and all references to this folder to customize your project name.Python-Requirements-License-Checker
Public templateAwesome-Neuraxle
PublicA curated list for resources on Neuraxle.Neuraxle-TensorFlow
PublicMachine-Learning-Figures
PublicNeuraxio
Public- 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
- Signal prediction with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier
- 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
- Auto-optimizing a neural net (and its architecture) on the CIFAR-100 dataset. Could be easily transferred to another dataset or another classification task.
python-conv-lib
PublicA 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.
- Using a U-Net for image segmentation, blending predicted patches smoothly is a must to please the human eye.
- Plugging TensorBoard in an autoencoder on the MNIST dataset for demonstrating t-SNE embeddings visualization of unsupervised machine learning.
- 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.
- 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.
- Simple demo of filtering signal with an LP filter and plotting its STFT and Laplace transform, in Python.
- Digit Recognition with scikit-learn's Bernoulli RBM and Logistic Classifier