TensorFlow, the open source library from Google, has been democratizing the world of machine intelligence since its launch last year. With TensorFlow, combined with the scalability of Google’s Cloud Machine Learning platform, now anyone can leverage deep learning technology cheaply and without much expertise. Kazunori Sato explores three examples of business that have adopted TensorFlow and Cloud ML to solve their real-world problems: a cucumber farmer in Japan who was able to build a deep learning-based cucumber sorter by himself, a used car auction service using TF for classifying car models and parts with 100x better training performance, and a global insurance company that has been able to increase prediction accuracy significantly on accident cases.
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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