xNLP driven AI is a fast-growing technology domain with diverse applications in customer engagement, employee collaboration, marketing, and social media. Does having an accurate model by itself mean, that we have a successful product, service, or solution? No! The most difficult phase begins after that. We still have the following challenges to solve. How do we Create a sellable service around this model? How to Scale this service to handle millions of inference requests, in a cost-effective manner? How to build automated deployment pipelines for software and models? How to add security, privacy, manageability, and observability for the service? How to track model drift and analyze model performance? In this session, we will discuss these questions and explore answers. We will go through the unique challenges that NLP serving poses and the solutions and best practices to overcome them.

This session was recorded at ODSC West, 2020, and present by Kumaran Ponnambalam


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Workshop Overview

  • 01

    Building a ML Serving Platform at Scale for Natural Language Processing

    • Workshop Overview and Author Bio

    • Goals and Session Agenda

    • An AI Architecture Framework & Contact Centers

    • Real-time Publishing & Stream Processing

    • Streaming NLP and NLU, and Orchestration

Instructor Bio:

Kumaran Ponnambalam

Kumaran Ponnambalam is a seasoned veteran in everything data, with a reputation for delivering high performance database and SaaS applications and currently specializing in leading Big Data Science and Engineering efforts

Kumaran Ponnambalam

Big Data & Data Science & Analytics Leader | Cisco