14–17 Oct 2019

Arun Kejariwal
Lead Engineer, Independent

Arun Kejariwal is an independent lead engineer. Previously, he was he was a statistical learning principal at Machine Zone (MZ), where he led a team of top-tier researchers and worked on research and development of novel techniques for install-and-click fraud detection and assessing the efficacy of TV campaigns and optimization of marketing campaigns, and his team built novel methods for bot detection, intrusion detection, and real-time anomaly detection; and he developed and open-sourced techniques for anomaly detection and breakout detection at Twitter. His research includes the development of practical and statistically rigorous techniques and methodologies to deliver high performance, availability, and scalability in large-scale distributed clusters. Some of the techniques he helped develop have been presented at international conferences and published in peer-reviewed journals.

Sessions

9:00–12:30 Tuesday, 15 October 2019

Location: Buckingham Room - Palace Suite

Herding cats: Product management in the machine learning era

AI Business Summit, Executive Briefing/Best Practices

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. Read more.

11:55–12:35 Wednesday, 16 October 2019

Location: King's Suite - Sandringham

Sequence to sequence (S2S) modeling for time series forecasting

Models and Methods

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. Read more.