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0523test

项目描述

2016ccf-stategrid

CCF2016 - TNT_000二等奖作品

2017-jdata-competition

高潜用户购买意向预测-rank12

2018-dc-datagrand-textintelprocess

2018-DC-“达观杯”文本智能处理挑战赛：冠军 (1st/3131)

2018-huawei-codecraft

2018-tencent-ad-competition-baseline

2018腾讯广告算法大赛baseline 线上0.73

algorithm_interview_notes-chinese

2018/2019/校招/春招/秋招/算法/机器学习(Machine Learning)/深度学习(Deep Learning)/自然语言处理(NLP)/C/C++/Python/面试笔记

astgcn

Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting (ASTGCN) AAAI 2019

awesome-fer

A reading list of top Conferences & Journals, focused on facial expression recognition (FER)

awesome-human-pose-estimation

A collection of awesome resources in Human Pose estimation.

awesome-semantic-segmentation

:metal: awesome-semantic-segmentation

booksource

《深度学习应用实战之PaddlePaddle》的源码

caffe-face

This branch is developed for deep face recognition

camera-openpose-keras

keras使用openpose模型的一个小例子 demo for kereas openpose

cascaded_mobilenet-v2

cascaded convolutional neural network for facial point detection

chfacerec

chFaceRec

chinese-character-recognition

This project shows how to use CNN to perform Chinese character recognition, a much more complicated task compared to MNIST digit recognition.

chinese_font_recognition

A base pipline for chinese recognition

chinese_poem_generator

唐诗、宋词生成器，有详细说明

cifar-10-cnn

Learn deep learning with CIFAR datasets

crackforest-dataset

crnn

Convolutional Recurrent Neural Network (CRNN) for image-based sequence recognition.

crowd-counting

Image Crowd Counting Using Convolutional Neural Network and Markov Random Field

crowd-counting-mcnn

A very ugly unofficial implementation of CVPR2016 paper Single-Image Crowd Counting via Multi Column Convolutional Neural Network using tensorflow and keras

crowd-counting-scnn

This project is an implementation of the crowd counting model proposed in our CVPR 2017 paper - Switching Convolutional Neural Network(SCNN) for Crowd Counting. SCNN is an adaptation of the fully-convolutional neural network and uses an expert CNN that chooses the best crowd density CNN regressor for parts of the scene from a bag of regressors. This helps it tackle intra-scene crowd density variation and obtain SOTA results

ctr_keras

LR, Wide&Deep, DCN, NFM, DeepFM, NFFM

daguan

2018达观杯文本智能处理挑战赛

daguan-1

“达观杯”文本智能处理挑战赛

data-competition-topsolution

Data competition Top Solution 数据竞赛top解决方案开源整理

data-science-notes

数据科学的笔记以及资料搜集