AutoML project, Google Inc., Mountain View, California, USA

Cloud AutoML is a suite of Machine Learning products that enables developers with limited machine learning expertise to train high quality models by leveraging Google’s state of the art transfer learning, and Neural Architecture Search technology.

AutoML Vision is the first product to be released. It is a simple, secure and flexible ML service that lets you train custom vision models for your own use cases. Soon, Cloud AutoML will release other services for all other major fields of AI.

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Amy Unruh and Sara Robinson join the podcast this week to talk with Mark and Melanie about the alpha launch of Cloud AutoML Vision. Cloud AutoML is a suite of products enabling developers with limited ML expertise to build high quality models using transfer learning and Neural Architecture Search techniques. AutoML Vision is the first product out the gate with a focus on making it easy to train customized vision models.

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In this episode of AI Adventures, Yufeng Guo uses AutoML Vision to build and employ a machine learning model that recognizes different types of….chairs! In part 1, he’ll walk you through gathering the data and creating a csv file that describes the location and label for all the images in the dataset. Don’t miss part 2 to see how the model performs!

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In part one of the AI Adventures intro to AutoML Vision, Yufeng talked about what AutoML Vision is used for and showed how to gather and prepare our training data. Stick around for part two where he shows how to use the data to train our model!

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