Wolff Dobson walks you through training and deploying a machine-learning system using TensorFlow, a popular open source library, and demonstrates how to build machine-learning systems from simple classifiers to complex image-based models.
Wolff begins by building a simple classifier in TensorFlow before introducing deep learning by training a complex model in TensorFlow. By comparing the results of the two models, you’ll gain insight into deep learning and learn how it can be applied to complex problems in science and industry. Wolff concludes with a hands-on demonstration of deploying a model in production using TensorFlow Serving, a high-performance open source system designed for serving machine-learned models.
Wolff Dobson is a developer programs engineer at Google specializing in machine learning and games. Previously, he worked as a game developer, where his projects included writing AI for the NBA 2K series and helping design the Wii Motion Plus. Wolff holds a PhD in artificial intelligence from Northwestern University.
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