Strata + Hadoop World 2016 – San Jose, California – Hardcore Data Science

Hardcore Data Science
Lessons learned from building real-life machine-learning systems – Xavier Amatriain (Quora) 00:32:06
The how and why of feature engineering – Alice Zheng (Dato) 00:26:22
A scalable implementation of deep learning on Spark – Alexander Ulanov (Hewlett-Packard Labs) 00:26:39
BIDMach on Spark: Machine learning at the outer limits – John Canny (UC Berkeley) 00:34:25
Dynamic memory networks for visual and textual question answering – Stephen Merity (MetaMind) 00:25:59
Scalable ensemble learning with H2O – Erin Ledell (H2O.ai) 00:27:14
Detecting and scoring anomalies with calibrated probabilistic models – Alexander Gray (Skytree, Inc.) 00:27:41
Scalable collective reasoning in graphs – Lise Getoor (University of California, Santa Cruz) 00:29:57
Phase retrieval algorithms for gigapixel microscopy – Laura Waller (UC Berkeley) 00:29:52
TensorFlow: Machine learning for everyone – Rajat Monga (Google) 00:24:54
A deep dive into DeepDive – Mike Cafarella (University of Michigan) 00:27:55

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