Abstract: As Gartner notes in the “State of Data Science and Machine Learning” report, DSML platforms are now addressing two growing and equally important markets: (i) A ‘multipersona’ market with a central focus on time to value, ease of use, and collaboration between multiple technical and nontechnical personas, and (ii) an ‘engineering’ market focused on primarily technical personas whose primary aim is to engineer (design, develop, deploy, monitor, and maintain) scalable, enterprise-wide AI solutions.
Discover what this means for businesses, data scientists and engineers in this talk. We will also discuss the processes involved and explore sample outputs/ deliverables achievable with such tools.
Bio: Hui Xiang Chua is Senior Data Scientist at Dataiku, helping enterprises with data democratization and enabling them to build their own path to AI. Dataiku is a 2x Gartner Magic Quadrant Leader for Data Science and Machine-Learning Platforms (as of 2021).
She has both public and private experiences solving problems using data, namely over six years in the public service and two years in the media industry. She was also previously an instructor with General Assembly.
In 2017, she was accepted to the Data Science for Social Good Fellowship and was mentored by Rayid Ghani, Chief Scientist of the Obama for America campaign in 2012. For bringing data science into a high school’s curriculum, Hui Xiang was a recipient of the KDD Impact Program award by SIGKDD, the Association for Computing Machinery’s special interest group on knowledge discovery and data mining. She also runs a data science blog called Data Double Confirm that was recognised as 2018/2019 Top 100 Data Science Resources on MastersInDataScience.com.
Hui Xiang holds a B.Sc.(Hons) in Statistics and M.Sc. in Business Analytics from National University of Singapore.