Machine Learning / AI Track Overview
As everyone reading this is aware, the Machine Learning / Artificial Intelligence space is fast-moving and highly, highly impactful. And this will only increase moving forward.
It’s also fascinating and incredibly interesting as open source plays a huge role in the technologies and processes underpinning it all.
While we’re still building out the final lineup to be featured, the speakers and talks already confirmed are ridiculously good. Take a look below and plan now to attend, and stay tuned as we confirm final speakers and topics in the weeks ahead.
Tuesday, November 1
Testing for Cognitive Bias in AI Systems
Gerie Owen, ZS
Combine the strengths of an Open Source Rules Engine and Machine Learning Platform to power decisioning
Andrew Bonham, Capital One
Machine Learning + Graph Databases for Better Recommendations
Christopher Woodward, ArangoDB
Go from “Paper” to Usable Data in Minutes with Python, OSS & Deep Learning
Frédéric Harper, Mindee
Mab2Rec: A library for building bandit-based recommenders
Bernard Kleynhans, Fidelity Investments