TensorFlow is an open source software library from Google for numerical computation using data flow graphs. It provides a flexible platform for defining and running machine-learning algorithms and is particularly well suited for building deep neural networks.
Amy Unruh and Eli Bixby offer practical, hands-on experience with TensorFlow. Amy and Eli start by providing some background and motivation for problems in machine learning and introduce some core TensorFlow concepts. Then, they dive into a deeper exploration of TensorFlow by building and training several different neural nets.
Amy Unruh is a developer programs engineer at Google for the Google Cloud Platform, where she works with TensorFlow as well as many other Cloud Platform technologies. Amy has a PhD in CS/AI, has worked in academia, at several startups, and in industrial R&D, and has published a book on App Engine.
Eli Bixby is a developer programs engineer at Google currently developing on Google Cloud Platform’s DevOps distributed systems, machine-learning, and big data offerings. He joined Google as a developer programs engineer. Previously, Eli dabbled in several research areas, with papers in biophysics, algorithmic game theory, and most recently computational biology.
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