The second data scientist at DataRobot Japan. He majored in quantum information theory as a master and doctoral student at universities in the UK and Canada. He has extensive experience in time series models, such as marketing and demand forecasting for major apparel companies and mail order companies. Cooperation with marketing technology, event lectures/interviews, etc.
2015-2017: Data Scientist @ Criteo-Data Science & Analytics Team Lead
2017-: Lead Data Scientist @ DataRobot, Inc.-Leading the retail and distribution industry
In recent years, machine learning models are often used in time series prediction. At Kaggle, competitions such as “ASHRAE-Great Energy Predictor III” and “Recruit Restaurant Visitor Forecasting” were among the top players in the XGB category. In this session, we will summarize the points of performing time series prediction using machine learning, such as partitioning, feature engineering and modeling.