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Hackntu_x_Cathay_2017

  • Thanks for everyone's attending!

introduction(pdf)

  • 資料介紹
  • 方向建議與實作
  • 商業分析

dataset (for preview purpose)

profile

field type Description
customer_id String 客戶 ID
birth_time Long 出生時間戳記
gender String 性別
contact_loc String 居住地區
contact_code String 居住地區郵遞區號代碼
register_loc String 戶籍地區
register_code String 戶籍地區郵遞區號代碼
start_time Long 起始往來時間戳記
aum Double 近三個月平均的總資產餘額
net_profit Double 近一年淨收益
credit_card_flag String 是否有信用卡產品往來
loan_flag String 是否有貸款產品往來
deposit_flag String 是否有存款產品往來
wealth_flag String 是否有理財產品往來
partition_time   Long   snapshot時間戳記    

sample

1,1871111837,F,D,181903,F,373933,3320438400,1217.1769900503969,528.7309192220683,Y,Y,N,N,3696969600

event

themes

  • cctxn
  • atm
  • cti
  • mybank
field type description
actor_type String 值皆是"customer_id"
actor_id String 行為者ID
action_type String 行為類型
action_time Long 行為發生時間戳記
object_type String 影響物件類型
object_id String 影響物件ID
channel_type String 通路類型
channel_id String 通路ID
attrs String 補充資料 - JSON string
partition_time Long 最近上一區段時間戳記 (可串連profile)
theme String 主題 - cc_txn, atm, cti, mybank

sample

customer_id,17,inquire,3696970704,saving_acct,MJQXLDJMQQOYAPFBBPBS,ATM,NCZHYDSTABCUAXLYJLQZ,"{\"action\": {\"txn_amt\": 0.0, \"txn_fee_amt\": 0.0, \"trans_type\": \"trans_out\"}, \"object\": {\"target_bank_code\": \"B_bank\", \"target_acct_nbr\": \"UMOTEPKACILAPBIKOYHZ\"}, \"channel\": {\"address_zipcode\": 601401, \"machine_bank_code\": \"C_bank\"}}",3696969600,atm

example

  • Easy Profiling
  • Wrangling data with Apache Spark

Already installed libraries in VM

Python 2.7

sklearn, numpy, pandas, jupyter, networkx, keras, tensorflow, flask, django, xgboost

R 3.3.3

xgboost

Java 1.7

Spark 2.1

node.js

IDE

sublime, pycharm, Rstudio

other reference

Credit Card

Spark

Python

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This repo is prepared for the HackNTU X Cathay 2017 Hackathon

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