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The official Jupyter Conference
August 22-23, 2017: Training
August 23-25, 2017: Tutorials & Conference
New York, NY

Cloud Datalab: Jupyter with the power of BigQuery and TensorFlow

Kaz Sato (Google)
11:55am–12:35pm Friday, August 25, 2017
Usage and application
 Location: Murray Hill Level: Beginner
Average rating: *****
(5.00, 1 rating)

Who is this presentation for?

  • Data scientists and data analysts

Prerequisite knowledge

  • A basic understanding of machine learning and big data processing

What you'll learn

  • Explore Google Cloud Datalab—a Jupyter environment from Google that integrates BigQuery, TensorFlow, and other Google Cloud services seamlessly

Description

Kazunori Sato explains how you can use Google Cloud Datalab—a Jupyter environment from Google that integrates BigQuery, TensorFlow, and other Google Cloud services seamlessly—to easily run SQL queries from Jupyter to access terabytes of data in seconds, train a deep learning model with TensorFlow with tens of GPUs in the cloud, and apply your models to the dataset with a little work, with all the usual tools available on Jupyter.

Photo of Kaz Sato

Kaz Sato

Google

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.