머신러닝, 딥러닝, 인공지능 연구소

1. (Kaggle Home Credit) top 1% with only 2 submissions? how?

   learning from arnowaczynski

   2018/08/31

2. Kaggle Santander Value Prediction TOP 8%

   The digitalization of everyday lives means that customers expect services to be delivered in a personalized and timely manner… and often before they´ve even realized they need the service. In their 3rd Kaggle competition, Santander Group aims to go a step beyond recognizing that there is a need to provide a customer a financial service and intends to determine the amount or value of the customer’s transaction. This means anticipating customer needs in a more concrete, but also simple and personal way. With so many choices for financial services, this need is greater now than ever before.

   2018/08/30

3. Kaggle Home Credit Default Risk TOP 6%

   Home Credit strives to broaden financial inclusion for the unbanked population by providing a positive and safe borrowing experience. In order to make sure this underserved population has a positive loan experience, Home Credit makes use of a variety of alternative data–including telco and transactional information–to predict their clients’ repayment abilities.

   2018/08/30

4. Kaggle Titanic Machine Learning from Disaster TOP 3%

   캐글(Kaggle)은 전세계에서 가장 큰 데이터 분석 경진 대회입니다.

   2018/07/10

5. Featuretools(automating feature engineering) in Python

   연구 중, 업로드 예정일 2018년 9월 30일

   2018/06/29

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