Sep 9–12, 2019
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.
9:00am–12:30pm Tuesday, September 10, 2019
Location: LL21 C/D
Secondary topics: Machine Learning
Ira Cohen (Anodot)
(3.50, 4 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 what it takes to manage ML-based products, the cycle of developing ML-based capabilities (or entire products), and the role of the (product) manager in each step of the cycle. Read more.
1:45pm–2:25pm Wednesday, September 11, 2019
Location: LL21 C/D
Secondary topics: Deep Learning, Machine Learning, Temporal data and time-series
Arun Kejariwal (Independent), Ira Cohen (Anodot)
(4.40, 5 ratings)
Sequence to sequence (S2S) modeling using neural networks is increasingly becoming mainstream. In particular, it's been leveraged 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 the aforementioned use cases, visualization, real-time anomaly detection, and forecasting. Read more.
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