Accelerate ML Feature Engineering through Automation
Accelerate ML Feature Engineering through Automation

Abstract: 

Applying Artificial Intelligence (AI) and Machine Learning (ML) has obvious benefits for many industries. However, the challenge is that developing the flat tables necessary to develop effective ML models is tedious, time-consuming, and prone to error. While AutoML platforms provide a convenient and rapid means of testing features against multiple ML algorithms, the task of building the needed feature tables has - until now - been exclusively manual. Join dotData's CEO and Founder, Dr. Ryohei Fujimaki PhD, as he discusses the future of Feature Engineering and how automation can provide a rapid means of testing use-cases, building feature pipelines, and creating a framework that helps financial institutions build ML/AI models in days - instead of months

Bio: 

Ryohei is the Founder & CEO of dotData. Prior to founding dotData, he was the youngest research fellow ever in NEC Corporation’s 119-year history, the title was honored for only six individuals among 1000+ researchers.

During his tenure at NEC, Ryohei was heavily involved in developing many cutting-edge data science solutions with NEC’s global business clients, and was instrumental in the successful delivery of several high-profile analytical solutions that are now widely used in industry.

Ryohei received his Ph.D. degree from the University of Tokyo in the field of machine learning and artificial intelligence.

Open Data Science

 

 

 

Open Data Science
One Broadway
Cambridge, MA 02142
info@odsc.com

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