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academic-kickstart

📝 Easily create a beautiful website using Academic, Hugo, and Netlify

active-learning

activelearning

advanced-deep-learning-with-python

Advanced Deep Learning with Python by Packt Publishing

amazon-sagemaker-examples

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

convolutional-nn

convolutional-rnn

TensorFlow code for the paper Convolutional RNN: an Enhanced Model for Extracting Features from Sequential Data (https://arxiv.org/abs/1602.05875)

cvnd_localization_exercises

Notebooks for learning about object motion and localization methods in the last section of CVND.

datasharing

The Leek group guide to data sharing

deeplearningflappybird

Flappy Bird hack using Deep Reinforcement Learning (Deep Q-learning).

engineering-blogs

A curated list of engineering blogs

faers-data

Data and basic scrubbing of the FDA Adverse Event Reporting System data

guardcell

guardcellsegmentation

3D Stomata Segmentation

hvae-nips

Code for the Hamiltonian Variational Auto-Encoder from the proceedings of NeurIPS 2018

ist597-deep-learning-

learnopencv

Learn OpenCV : C++ and Python Examples

libact

Pool-based active learning in Python

machine-learning-overview

machinelearning-uw

Solutions for Machine Learning Specialization MOOC offered by University of Washington.

medical-report-generation

A pytorch implementation of On the Automatic Generation of Medical Imaging Reports.

mnist-recognition-

probabilistic-programming-and-bayesian-methods-for-hackers

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

r_workshop

semantic-segmentation-suite

Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!

semanticsegmentation

stargan

StarGAN - Official PyTorch Implementation (CVPR 2018)

synlab

1D synchrosqueezed wave packet transforms (SSWPT): Analyzing instantaneous properties (instantaneous frequencies, phases and amplitudes) of non-linear oscillatory signals in a superposition. 2D synchrosqueezed curvelet transform (SSCT): Anlayzing local properties of non-linear oscillatory textures in a superposition.

texar

Toolkit for Machine Learning, Natural Language Processing, and Text Generation, in TensorFlow. This is part of the CASL project: http://casl-project.ai/

unet

U-Net Model for Image Segmentation Problems using PyTorch 0.4