October 28–31, 2019
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TensorFlow Lite: Solution for running ML on-device

Pete Warden (Google), Nupur Garg (Google), Matthew DuPuy (Arm)
11:50am12:30pm Thursday, October 31, 2019
Location: Great American Ballroom J/K
Average rating: ****.
(4.00, 2 ratings)

Who is this presentation for?

  • Mobile app developers and hardware and software makers


New to TensorFlow


Pete Warden, Nupur Garg, and Matthew Dupuy take you through TensorFlow Lite, TensorFlow’s lightweight cross-platform solution for mobile and embedded devices. It enables on-device machine learning inference with low latency, high performance, and a small binary size. It’s the standard solution at Google and the primary inference framework for all on-device use cases.

Prerequisite knowledge

  • Familiarity with ML

What you'll learn

  • Learn how TensorFlow Lite tools work and how to convert and optimize models for mobile and embedded devices
Photo of Pete Warden

Pete Warden


Pete Warden is the technical lead of the mobile and embedded TensorFlow Group on Google’s Brain team.

Photo of Nupur Garg

Nupur Garg


Nupur Garg is a software engineer on the TensorFlow Lite team at Google Brain. She holds an MS in computer science from Cal Poly in San Luis Obispo.

Photo of Matthew DuPuy

Matthew DuPuy


Matthew Du Puy has been a software engineer at Arm for 8 years and is currently working on AI at the edge and IoT technology. Previously he worked on Android, open-source math libraries and the Linux Kernel. He is also the second American to have climbed Annapurna, K2, and Everest.

  • O'Reilly
  • TensorFlow
  • Google Cloud
  • IBM
  • Databricks
  • Tensor Networks
  • VMware
  • Amazon Web Services
  • One Convergence
  • Quantiphi
  • Lambda Labs
  • Tech Mahindra
  • cnvrg.io
  • Determined AI
  • Inferencery
  • Manceps, Inc.
  • PerceptiLabs
  • Valohai

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