Automated Feature Engineering for Enterprise Machine Learning


Good machine learning algorithms don’t guarantee good models. Great models need great features. That’s why feature engineering takes so much time. Developing good features is time-consuming, difficult, and most of all requires domain knowledge. Join dotData CEO, Ryohei Fujimaki, PhD, as he discusses the future of Feature Engineering, how automation can help you extract the full-potential of your data, and how you can leverage AI-features to augment and reinforce your AI/ML workflow.


Aaron is currently the Vice President of Data Science and Solutions at dotData. As a data science practitioner with 14 years of research and industrial experience, he has held various leadership positions in spearheading new product development in the fields of data science and business intelligence. At dotData, Aaron leads the data science team in working directly with clients and solving their most challenging problems.

Open Data Science




Open Data Science
One Broadway
Cambridge, MA 02142

Privacy Settings
We use cookies to enhance your experience while using our website. If you are using our Services via a browser you can restrict, block or remove cookies through your web browser settings. We also use content and scripts from third parties that may use tracking technologies. You can selectively provide your consent below to allow such third party embeds. For complete information about the cookies we use, data we collect and how we process them, please check our Privacy Policy
Consent to display content from - Youtube
Consent to display content from - Vimeo
Google Maps
Consent to display content from - Google