Presented By
O’Reilly + Cloudera
Make Data Work
March 25-28, 2019
San Francisco, CA
Aashish Sheshadri

Aashish Sheshadri
Research Engineer, PayPal

Website

Aashish Sheshadri is a research engineer at PayPal, where he currently ideates and applies deep learning to new avenues and actively contributes to the Jupyter ecosystem and the SEIF Project. He holds an MS in computer science from the University of Texas at Austin, where his research focused on active learning with human-in-the-loop systems.

Sessions

1:50pm–2:30pm Thursday, March 28, 2019
On a deep journey toward five nines
Data Science, Machine Learning & AI
 Location: 2016
Secondary topics:  Deep Learning, Financial Services, Temporal data and time-series analytics
Aashish Sheshadri (PayPal)
Average rating: ****.
(4.50, 2 ratings)
Deep learning using sequence-to-sequence networks (Seq2Seq) has demonstrated unparalleled success in neural machine translation. A less explored but highly sought-after area of forecasting can leverage recent gains made in Seq2Seq networks. Aashish Sheshadri explains how PayPal has applied deep networks to monitoring and alerting intelligence. Read more.