BigQuery is Google’s fully managed, petabyte-scale, low-cost enterprise data warehouse. By leveraging the petabit network and tens of thousands of servers in Google’s data center, BigQuery allows you to execute your SQL as a massively parallel processing query with hundreds of CPU cores and ample disk storage, scanning and aggregating terabytes of data in seconds.
Kazunori Sato demonstrates how to integrate UDF with BigQuery, TensorFlow, and ML Engine and build a powerful solution with cloud data warehouses and machine learning.
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 and Hadoop World 2016, and Google Next 2015 NYC and Tel Aviv, and he has hosted FPGA meetups since 2013.
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