DataHour: Optimizing Real-Time ML Inference with Nvidia Triton Inference Server

DataHour: Optimizing Real-Time ML Inference with Nvidia Triton Inference Server

26 Feb 202309:02am - 26 Feb 202310:02am

DataHour: Optimizing Real-Time ML Inference with Nvidia Triton Inference Server

About the Event

Hosting ML Models as an API service is one of the ML model serving patterns when a model is trained offline but hosted for on-demand predictions.

Challenges of Real-time inferencing include but are not limited to strict latency constraints, high throughput and high availability assurances, and expectations of auto-scaling to accommodate changes in the volume of incoming requests.

There are multiple solutions in the market for ML model serving - TF Serving, TorchServe, and Seldon core. 

In this DataHour, Sharmili will introduce you to one such Inference server from Nvidia - Triton Inference Server. She will also walk you through the distinguishing features of Triton that makes it powerful.


Prerequisites:
 Basic understanding of Docker containers fundamentals (101) and python programming and enthusiasm of learning Data Science and Deep Learning. 

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Who is this DataHour for?

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About the Speaker

Sharmili Srinivasan

Sharmili Srinivasan

ML Engineer at PayPal

With 8+ years of experience in building scalable end-to-end ML systems across multiple sectors of finance, telecom, and software products, Sharmili is currently leading the ML Engineering team in Customer Success Platform – Data Science, PayPal.Prior to PayPal, she has worked with various MNC’s including Ericsson, Freshworks, TCS etc. 

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