14–17 Oct 2019

Ira Cohen
Cofounder, Chief Data Scientist, Anodot
Ira Cohen is a cofounder and chief data scientist at Anodot, where he’s responsible for developing and inventing the company’s real-time multivariate anomaly detection algorithms that work with millions of time series signals. He holds a PhD in machine learning from the University of Illinois at Urbana-Champaign and has over 12 years of industry experience.
Sessions
9:00–12:30 Tuesday, 15 October 2019
Location: Buckingham Room - Palace Suite
Secondary topics:
Machine Learning
Ira Cohen (Anodot),
Arun Kejariwal (Independent)
Average rating:









(3.25, 8 ratings)
While the role of the manager doesn't require deep knowledge of ML algorithms, it does require understanding how ML-based products should be developed. Ira Cohen explores the cycle of developing ML-based capabilities (or entire products) and the role of the (product) manager in each step of the cycle.
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11:55–12:35 Wednesday, 16 October 2019
Location: King's Suite - Sandringham
Secondary topics:
Deep Learning,
Machine Learning,
Temporal data and time-series
Arun Kejariwal (Independent),
Ira Cohen (Anodot)
Average rating:









(4.00, 5 ratings)
Sequence to sequence (S2S) modeling using neural networks has become increasingly mainstream in recent years. In particular, it's been used for applications such as speech recognition, language translation, and question answering. Arun Kejariwal and Ira Cohen walk you through how S2S modeling can be leveraged for these use cases, visualization, real-time anomaly detection, and forecasting.
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