guillaume-chevalier/CS-Games-2018-Google-Challenge-TensorFlow guillaume-chevalier/CS-Games-2018-Google-Challenge-TensorFlow

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guillaume-chevalier/CS-Games-2018-Google-Challenge-TensorFlow
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1

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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
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2

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3

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Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier
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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.
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6

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.
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7

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8

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9

GloVe-as-a-TensorFlow-Embedding-Layer

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11

ReuBERT

A question-answering chatbot, simply.
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12

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.
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13

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Assessing personal growth on LinkedIn with charts. Plot LinkedIn connections over time. Discover what your connections most do and where they most work.
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14

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
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15

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Predict whether income exceeds $50K/yr based on census data of the "Adult Dataset". Also known as "Census Income" dataset.
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16

AI-Planning-Solver-Shakeys-World-PDDL

Solving a planning problem (Shakey's World) with the FF and IPP planners, the PDDL language and some Python meta-programming to glue things together.
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17

EDA-for-Cybersecurity-Intrusion-Detection-KDD-Cup-99

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18

caffe-cifar-10-and-cifar-100-datasets-preprocessed-to-HDF5

Both deep learning datasets can be imported in python directly with h5py (HDF5 format). The datasets can be directly imported or converted with a python script.
Python
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19

python-caffe-custom-cifar-100-conv-net

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.
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20

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.
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21

SGNN-Transformer-Sentence-Model-SimilarityBXEnt

SGNN-Transformer Sentence Model trained by the paragraph-skip-gram-like SimilarityBXENT. Also see: https://github.com/guillaume-chevalier/SGNN-Self-Governing-Neural-Networks-Projection-Layer
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22

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23

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25

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26

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27

XGBoost-Beer-Recommendation

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28

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