Flink Forward 2016: Trevor Grant - Apache Zeppelin: A friendlier way to Flink
#FlinkForward SF 2017: Trevor Grant - Introduction to Online Machine Learning Algorithms
Flink Forward 2016: Ted Dunning - Keynote: How Can We Take Flink Forward?
Flink Forward 2016: Ted Dunning - Faster and Furiouser: Flink Drift
Flink Forward 2016: Steve Blackmon - Large Scale Social Network Data Collection & Analysis...
Flink Forward 2016: Kostas Tzoumas & Stephan Ewen - Keynote
Flink Forward 2016: Ana M. Martinez - AMIDST Toolbox: Scalable probabil. machine learning w/ Flink
Flink Forward 2016: Jamie Grier - The Stream Processor as a Database
Do I Know You? Real time facial recognition with an Apache stack - Trevor Grant (IBM)
Flink Forward 2016: Márton Balassi - Streaming ML with Flink
Bring Flink to Large Scale Production - Xiaowei Jiang (Alibaba)
#FlinkForward SF 2017: Ufuk Celebi - The Stream Processor as a Database
#FlinkForward SF 2017: Shaoxuan Wang & Xiaowei Jiang - Blinks Improvements to Flink SQL And TableAPI
#FlinkForward SF 2017: Stephan Ewen - Convergence of real-time analytics & data-driven applications
Using Queryable State to update ML Algorithms per datapoint for... - Warmerdam & Driesprong
TouK Nussknacker – creating Flink jobs with GUI - Maciek Próchniak
#FlinkForward SF 2017: Scott Kidder - Building a Real-Time Anomaly-Detection System with Flink @ Mux
#FlinkForward SF 2017: S. Sundararaman - Experiences w/ Streaming vs Micro-Batch for Online Learning
Flink Forward SF 2017: Jamie Grier - Apache Flink: The Latest and Greatest
#FlinkForward SF 2017: Ted Dunning - Non-Flink Machine Learning on Flink