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2018-ccf-bdci-china-unicom-research-institute-top2

2018-CCF大数据与计算智能大赛-面向电信行业存量用户的智能套餐个性化匹配模型联通赛-复赛第二名-【多分类，embedding】

2018-orange-financial-big-data-top9

2018年甜橙金融杯大数据建模大赛-初赛第四-复赛线上11-决赛9-复现top1解决方案-【二分类，风控】

4th-place-home-credit-default-risk

Codes and dashboards for 4th place solution for Kaggle's Home Credit Default Risk competition

ai-learn

人工智能学习路线图，整理近200个实战案例与项目，免费提供配套教材，零基础入门，就业实战！包括：Python，数学，机器学习，数据分析，深度学习，计算机视觉，自然语言处理等热门领域

al_challenger_2018_sentiment_analysis

AI Challenger 2018 细粒度用户评论情感分析，排名17th，基于Aspect Level 思路的解决方案

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

bat_interviews

:blue_book:分享最新BAT面试题(包含机器学习,Linux,PHP,大数据,Python,Java,前端...),持续更新ing...

bdc_2018

Preliminary rank_13

bdci2017

2017年CCF大数据与计算智能大赛-小超市供销存管理优化

bdci_car_2018

BDCI 2018 汽车行业用户观点主题及情感识别 《Just a test》团队方案-决赛第一名

bert

TensorFlow code and pre-trained models for BERT

book

Deep Learning 101 with PaddlePaddle （深度学习框架入门教程）

cc_fraud_proj

Playing with the IEEE-CIS Vesta fraud detection competition

ccf-bdci-sentiment-analysis-baseline

The code for CCF-BDCI-Sentiment-Analysis-Baseline

ccf-car

汽车行业用户观点主题及情感识别

ccf_2020_qa_match

ccf 2020 qa match competition top1

cf_gbdt_lr

简单的实现推荐系统的召回模型和排序模型，其中召回模型使用协同过滤算法，排序模型使用gbdt+lr算法

cgnn

Crystal Graph Neural Networks

competition

参加过的比赛记录，包括代码和经验和其他文件

context-aware-multi-modal-transportation-recommendation

KDD CUP 2019 Baseline

credit-scoring-regression

消费者人群画像—信用智能评分比赛开源

cs224n

CS224n: Natural Language Processing with Deep Learning Assignments Winter, 2017

cs231n

ctr_prediction

CTR prediction using FM FFM and DeepFM

data-competition-topsolution

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

dcic-failure-prediction-of-concrete-piston-for-concrete-pump-vehicles

Traditional approaches to production equipment maintenance remain mainly in corrective maintenance and routine-based maintenance. Corrective maintenance, which is no fail no repair, implies unscheduled downtime of equipment, severe security risk and unacceptable economic loss, while routine or time-based maintenance is time consuming and costly. By data analysis and modeling, predictive maintenance forecasts the residual life or possible failure of key components, and schedules maintenance accordingly，in order to avoid unscheduled downtime and to save cost.

dcic-the-estimation-of-scada-data-loss-in-offshore-wind-farm

We extract actual SCADA data of a certain offshore wind farm and artificially remove some of the data, including but not limited to deleting all data of a certain time period, data of a certain turbine at a certain time, some fields of a certain turbine at a certain time, etc. The applicant needs to use the remaining data to recover the deleted data, and the accuracy of the recovery shall be the final evaluation benchmark

deepctr

Easy-to-use,Modular and Extendible package of deep-learning based CTR models.DeepFM,DeepInterestNetwork(DIN),DeepCrossNetwork(DCN),AttentionalFactorizationMachine(AFM),Neural Factorization Machine(NFM),AutoInt

face_recognizer

face recognition application

flink

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