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algorithms

The implementation of some algorithms

caffe2

Caffe2 is a lightweight, modular, and scalable deep learning framework.

codecraft2018

2018华为软件精英挑战赛 - 围观的咸鱼 - 江山复赛8th

cs131_release

Released assignments for the fall 2017 iteration of CS131.

cs231n.github.io

Public facing notes page

deeplearning_research

the implementation of some deep learning algorithms

deeplearningbook-chinese

Deep Learning Book Chinese Translation

fcn.tensorflow

Tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation (http://fcn.berkeleyvision.org)

feature-selection

Features selection algorithm based on self selected algorithm, loss function and validation method

fish-eye-image-correction-code

This is my paper "Correction of single circular fisheye image" related program code

free-programming-books-zh_cn

:books: 免费的计算机编程类中文书籍，欢迎投稿

ijcai-18

2018 阿里妈妈搜索广告转化率预估　复赛最终成绩　rank 84/5204

imgaug

Image augmentation for machine learning experiments.

incubator-mxnet

Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

jdata

京东JData算法大赛-高潜用户购买意向预测入门程序(starter code)

jdata_2018

JData 2018 如期而至-用户购买时间预测　rank 27/5182

keras

Deep Learning library for Python. Runs on TensorFlow, Theano, or CNTK.

keras-squeezenet

SqueezeNet implementation with Keras Framework

learn

Learn git

learnviorb

lee-slam-source

SLAM 开发学习资源与经验分享

lihang_book_algorithm

致力于将李航博士《统计学习方法》一书中所有算法实现一遍

models

Models and examples built with TensorFlow

monocular-depth-estimation-with-dl

图像深度估计开源算法 剖析注释

monodepth-pytorch

Unofficial implementation of Unsupervised Monocular Depth Estimation neural network MonoDepth in PyTorch

readme

README文件语法解读，即Github Flavored Markdown语法介绍

readmelearn

How to write README.md in GitHub.

samples-for-ai

Samples for getting started with deep learning across TensorFlow, CNTK, Theano and more.

scheduler_2018

阿里巴巴全球调度算法大赛 rank 14/2116

tensorflow-deepfm

Tensorflow implementation of DeepFM for CTR prediction.