Speaker "Steven Gustafson" Details Back



Automated Machine Learning (AutoML) for Data Science Productivity


With the increased availability of both cloud computing and AI libraries arrives the opportunity to automatically search, or optimize machine learning algorithms. While this technology has been around for almost twenty years and seeing renewed interest lately, only recently has the computing power become widespread enough to fully take advantage of it by a growing community of data scientists across many different types of opportunities. Because machine learning still remains a rather challenging discipline for most, I advocate for a more “assistive” approach to AutoML that helps the data scientist learn about different methods within the entire machine learning pipeline, as well as create a knowledge graph of results that can be further mined and explored to gain knowledge and connect with other individuals who are also searching for machine learning pipelines. In this talk, I will present an overview of the approach, published recently in IJCAI and AAAI, and provide new unpublished results demonstrating its effectiveness on public data sets.

Who is this presentation for?
Technologists and leaders in the data science organization.
Prerequisite knowledge:
Basic understanding of the data science workflow and organization.
What you'll learn?
Why AutoML goes beyond parameter optimization to a source of critical knowledge capture.


Dr. Gustafson is the CTO at Noonum, a FinTech startup that delivers insights on companies and markets using advances in NLP and AI. He received his PhD in Computer Science and Artificial Intelligence  from the University of Nottingham, UK, where he was a research fellow in the Automated Scheduling, Optimisation and Planning Research Group.   Shortly thereafter, Dr Gustafson was awarded IEEE Intelligent System's "AI's 10 to Watch" for his work in algorithms that discover algorithms. For 10+ years at GE's corporate R&D center he was a leader in AI, successful technical lab manager, all while inventing and deploying state-of-the-art AI systems for almost every GE business, from GE Capital to NBC Universal and GE Aviation. He has over 50 publications, 13 patents, was a co-founder and Technical Editor in Chief of the Memetic Computing Journal. As the Chief Scientist at a Knowledge Platform software company for 3 years, he invented and architected new AutoML and NLP microservices for industrial customers while growing an international data science and research team. With a passion for solving problems and innovation, Steven is excited about Noonum's opportunity to use AI to deliver insights and enable better decisions in financial markets and other industries.