October 28–31, 2019
Kaz Sato

Kaz Sato
Staff Developer Advocate, Google

Website | @kazunori_279

Kaz Sato is a staff developer advocate on the cloud platform team at Google, where he leads the developer advocacy team for machine learning and data analytics products such as TensorFlow, the Vision API, and BigQuery. Kaz has been leading and supporting developer communities for Google Cloud for over seven years. He’s a frequent speaker at conferences, including Google I/O 2016, Hadoop Summit 2016 San Jose, Strata + Hadoop World 2016, and Google Next 2015 NYC and Tel Aviv, and he has hosted FPGA meetups since 2013.


1:40pm2:20pm Wednesday, October 30, 2019
Location: Grand Ballroom E
Kaz Sato (Google)
Kaz Sato walks you through AutoML Vision, which allows you to upload labeled images, press a "train" button, and wait for a day to get an image recognition model with state-of-the-art accuracy. Without any ML expertise, you can easily train the model in the cloud, export the TensorFlow Lite model, and use it on mobile devices, Rasberry Pi, and Edge TPU with super low latency and power consumption. Read more.
2:30pm3:10pm Wednesday, October 30, 2019
Location: Grand Ballroom G
Karthik Ramachandran (Google Cloud), Kaz Sato (Google)
Karthik Ramachandran and Kaz Sato take a look at how you can use AI platform notebooks, deep learning virtual machines, and deep learning containers to build TensorFlow applications. You'll learn to maximize TensorFlow performance on Google Cloud by eliminating I/O bottlenecks and some tips and tricks for ensuring the longevity and reliability of your AI-powered enterprise applications. Read more.
  • 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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