This session was recorded in NYC on October 22nd, 2019 and can be viewed here: https://www.youtube.com/watch?v=eF4Oa0ZzXdQ&list=PLNtMya54qvOE3AvWRCNF2tybxNobUbAYp&index=6&t=3s
Time Series in H2O Driverless AI
Time series is a unique field in predictive modelling where standard feature engineering techniques and models are employed to get the most accurate results. In this session we will examine some of the most important features of Driverless AI’s newest recipe regarding Time Series. It will cover validation strategies, feature engineering, feature selection and modelling. The capabilities will be showcased through several cases.
Bio: Dmitry has more than 10 years of experience in IT. Starting with data warehousing and BI, now in big data and data science.He has a lot of experience in predictive analytics software development for different domains and tasks.
He is also a Kaggle Grandmaster who loves to use his machine learning and data science skills on Kaggle competitions.