phecy Goto Github PK

graphsage

Representation learning on large graphs using stochastic graph convolutions.

grasp-and-lift-eeg-challenge

Code and documentation for the winning sollution at the Grasp-and-Lift EEG Detection challenge

grpc

The C based gRPC (C++, Node.js, Python, Ruby, Objective-C, PHP, C#)

handong1587.github.io

horovod

Distributed training framework for TensorFlow.

hypergan

A composable Generative Adversarial Network(GAN) with API and command line tool.

id-fits

ift6266

Emotion Recognition

image-gpt

imagenet-adversarial-training

ImageNet classifier with state-of-the-art adversarial robustness

imagesorter

Analyze and assess technical quality of images

imgaug

Image augmentation for machine learning experiments.

imgclsmob

Sandbox for training convolutional networks for computer vision

industry-machine-learning

A curated list of applied machine learning and data science notebooks and libraries across different industries.

jade

A computer vision project to infer people's gender, age, and personality traits from Facebook profile photos.

javacpp-presets

The missing bridge between Java and native C++ libraries

jetson-inference

Guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and Jetson TX1/TX2.

jwnl-tests

kaggle-avazu

2nd place solution for Avazu click-through rate prediction competition

kaggle-galaxies

Winning solution for the Galaxy Challenge on Kaggle (http://www.kaggle.com/c/galaxy-zoo-the-galaxy-challenge)

kaggle_crowdflower

1st Place Solution for Search Results Relevance Competition on Kaggle (https://www.kaggle.com/c/crowdflower-search-relevance)

kcws

Deep Learning Chinese Word Segment

learning-to-learn

TensorFlow implementation of the paper "Learning to learn by gradient descent by gradient descent ( https://arxiv.org/abs/1606.04474 )"

lectures

Oxford Deep NLP 2017 course

libfm

Library for factorization machines

libshorttext

My fork of libshorttext

libvips

A fast image processing library with low memory needs.

llama

Inference code for LLaMA models

loss-landscape

Code for visualizing the loss landscape of neural nets

mae

PyTorch implementation of MAE https//arxiv.org/abs/2111.06377