Jupyter Notebook (Primary Language)

workshops f18 ^{🔗 ❐}

by McGillAISociety ^{🔗 ❐}

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teaching material ^{🔗 ❐}

by mtl-brainhack-school-2018 ^{🔗 ❐}

slides and notebooks for tutorials and pitches

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minc keras ^{🔗 ❐}

by tfunck ^{🔗 ❐}

minc_keras is a code base that was developped during a hackathon to facillitate the implementation of deep learning models for brain imaging with the Keras package.

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ICR detection in filled form ^{🔗 ❐}

by doxakis ^{🔗 ❐}

Automatically detect paper-based form fields

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glo4030 labs ^{🔗 ❐}

by ulaval-damas ^{🔗 ❐}

Laboratoires du cours GLO-4030/GLO-7030

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dl eeg playground ^{🔗 ❐}

by NeuroTechX ^{🔗 ❐}

Deep Learning EEG Playground

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flyingpigeon ^{🔗 ❐}

by bird-house ^{🔗 ❐}

WPS processes for climate model data, indices and extreme events

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miniscoPy ^{🔗 ❐}

by PeyracheLab ^{🔗 ❐}

A package to analyse calcium imaging data recorded with the Miniscope.

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ecolehiver2018 ^{🔗 ❐}

by mila-udem ^{🔗 ❐}

Ivado École d'hiver IVADO/MILA en apprentissage profond 2018

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scona ^{🔗 ❐}

by WhitakerLab ^{🔗 ❐}

Code to analyse structural covariance brain networks using python.

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axondeepseg ^{🔗 ❐}

by neuropoly ^{🔗 ❐}

Axon/Myelin segmentation using Deep Learning

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qgen workshop ^{🔗 ❐}

by Maluuba ^{🔗 ❐}

ImplementAI Workshop on Deep NLP for Question Generation

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reptile pytorch ^{🔗 ❐}

by gabrielhuang ^{🔗 ❐}

A PyTorch implementation of OpenAI's REPTILE algorithm

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form segmentation ^{🔗 ❐}

by doxakis ^{🔗 ❐}

Let's explore how we can extract text from forms

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gmseg ^{🔗 ❐}

by neuropoly ^{🔗 ❐}

Spinal cord gray matter segmentation using deep dilated convolutions.

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pytorch ntm ^{🔗 ❐}

by loudinthecloud ^{🔗 ❐}

Neural Turing Machines (NTM) - PyTorch Implementation

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ScientificComputingForTheRestOfUs ^{🔗 ❐}

by tpoisot ^{🔗 ❐}

Introduction to Scientific Computing 🦊

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montreal open data ^{🔗 ❐}

by tsloan1377 ^{🔗 ❐}

A place to host my ongoing analysis of Montreal commute data from the Montreal Open Data Portal

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TheConsciousnessPrior ^{🔗 ❐}

by AI-ON ^{🔗 ❐}

AI-ON Consciousness Prior

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generative query network pytorch ^{🔗 ❐}

by wohlert ^{🔗 ❐}

Generative Query Network (GQN) in PyTorch as described in "Neural Scene Representation and Rendering"

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welcome tutorials ^{🔗 ❐}

by mila-udem ^{🔗 ❐}

Various tutorials given for welcoming new students at MILA.

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Integrated Gradients ^{🔗 ❐}

by ankurtaly ^{🔗 ❐}

Attributing predictions made by the Inception network using the Integrated Gradients method

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Tutorials ^{🔗 ❐}

by iamtrask ^{🔗 ❐}

DEPRECATED - DO NOT USE

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tf playground ^{🔗 ❐}

by MtDersvan ^{🔗 ❐}

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gumbel softmax ^{🔗 ❐}

by ericjang ^{🔗 ❐}

categorical variational autoencoder using the Gumbel-Softmax estimator

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understanding pytorch batching lstm ^{🔗 ❐}

by ngarneau ^{🔗 ❐}

Understanding and visualizing PyTorch Batching with LSTM

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examples ^{🔗 ❐}

by kubeflow ^{🔗 ❐}

A repository to host extended examples and tutorials

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trpo ^{🔗 ❐}

by pat-coady ^{🔗 ❐}

Trust Region Policy Optimization with TensorFlow and OpenAI Gym

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dog project ^{🔗 ❐}

by udacity ^{🔗 ❐}

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tensorflow without a phd ^{🔗 ❐}

by GoogleCloudPlatform ^{🔗 ❐}

A crash course in six episodes for software developers who want to become machine learning practitioners.

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RL Adventure ^{🔗 ❐}

by higgsfield ^{🔗 ❐}

Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL

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annotated transformer ^{🔗 ❐}

by harvardnlp ^{🔗 ❐}

http://nlp.seas.harvard.edu/2018/04/03/attention.html

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fastai deeplearn part1 ^{🔗 ❐}

by reshamas ^{🔗 ❐}

Notes for Fastai Deep Learning Course

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pelican ipynb ^{🔗 ❐}

by danielfrg ^{🔗 ❐}

Pelican plugin for blogging with Jupyter/IPython Notebooks

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pangeo ^{🔗 ❐}

by pangeo-data ^{🔗 ❐}

Pangeo website + discussion of general issues related to the project.

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pomegranate ^{🔗 ❐}

by jmschrei ^{🔗 ❐}

Fast, flexible and easy to use probabilistic modelling in Python.

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ipyvolume ^{🔗 ❐}

by maartenbreddels ^{🔗 ❐}

3d plotting for Python in the Jupyter notebook based on IPython widgets using WebGL

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60 Days RL Challenge ^{🔗 ❐}

by andri27-ts ^{🔗 ❐}

Learn Deep Reinforcement Learning in Depth in 60 days

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iTorch ^{🔗 ❐}

by facebookarchive ^{🔗 ❐}

IPython kernel for Torch with visualization and plotting

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functional zoo ^{🔗 ❐}

by szagoruyko ^{🔗 ❐}

PyTorch and Tensorflow functional model definitions

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got book 6 ^{🔗 ❐}

by zackthoutt ^{🔗 ❐}

LSTM trained on the first five ASOIAF/GOT books

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practical pytorch ^{🔗 ❐}

by spro ^{🔗 ❐}

PyTorch tutorials demonstrating modern techniques with readable code

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fastai ^{🔗 ❐}

by fastai ^{🔗 ❐}

The fast.ai deep learning library, lessons, and tutorials

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lucid ^{🔗 ❐}

by tensorflow ^{🔗 ❐}

A collection of infrastructure and tools for research in neural network interpretability.

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mxnet the straight dope ^{🔗 ❐}

by zackchase ^{🔗 ❐}

An interactive book on deep learning. Much easy, so MXNet. Wow.

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dopamine ^{🔗 ❐}

by google ^{🔗 ❐}

Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.

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Augmentor ^{🔗 ❐}

by mdbloice ^{🔗 ❐}

Image augmentation library in Python for machine learning.

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pyfolio ^{🔗 ❐}

by quantopian ^{🔗 ❐}

Portfolio and risk analytics in Python

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