zhuiyuan616124 Goto Github PK

ctr

IJCAI-18 阿里妈妈搜索广告转化预测

ctr-paper-list

ctr_prediction

CTR prediction using FM FFM and DeepFM

daguan_cup

datacastle-solution

1st Place Solution for DataCastle-CashBus Competition

datacastle_subsidy

Datacastle助学金精准预测冠军代码

deep-learning-for-recommendation-systems

This repository contains Deep Learning based articles , paper and repositories for Recommender Systems

deep-learning-papers-reading-roadmap

Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

deepconvlstm

Deep learning framework for wearable activity recognition based on convolutional and LSTM recurretn layers

deeplearninginfinance

deepwalk

DeepWalk - Deep Learning for Graphs

deep_trader

This project uses reinforcement learning on stock market and agent tries to learn trading. The goal is to check if the agent can learn to read tape. The project is dedicated to hero in life great Jesse Livermore.

display-advertising-challenge

Criteo/Kaggle Competition of CTR prediction

dogs_vs_cats

猫狗大战

download

🔴蓝灯最新版本下载 https://github.com/getlantern/download 🔴 Lantern Latest Download https://github.com/getlantern/lantern/releases/tag/latest 🔴

dsb17-walkthrough

An end-to-end walkthrough of the winning submission by grt123 for the Kaggle Data Science Bowl 2017

dsb2017

Code for 2nd place solution to the 2017 National Data Science Bowl

dsb2017-1

The solution of team 'grt123' in DSB2017

ebooks

我的大数据学习书单

ensemble-learning

stacking&blending

ezshop

face-track-detect-extract

💎 Detect , track and extract the optimal face in multi-target faces (exclude side face and select the optimal face).

fcn.berkeleyvision.org

Fully Convolutional Networks for Semantic Segmentation by Jonathan Long*, Evan Shelhamer*, and Trevor Darrell. CVPR 2015 and PAMI 2016.

fitml

A collection of python Machine Learning articles and examples. You will find code related to Reinforcement Learning, Q Learning, MDP, Bellman, OpenAI solutions and others

hangzhou_house_knowledge

2017年买房经历总结出来的买房购房知识分享给大家，希望对大家有所帮助。买房不易，且买且珍惜。Sharing the knowledge of buy an own house that according to the experience at hangzhou in 2017 to all the people. It's not easy to buy a own house, so I hope that it would be useful to everyone.

har-stacked-residual-bidir-lstms

Using deep stacked residual bidirectional LSTM cells (RNN) with TensorFlow, we do Human Activity Recognition (HAR). Classifying the type of movement amongst 6 categories or 18 categories on 2 different datasets.

ijcai17_tianchi_rank4

ijcai_2018

初赛第10名，复赛第16名解决方案

ijcai_cup_2017

IJCAI-17 口碑商家客流量预测

jdd_loan_forecasting

京东借贷需求预测