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'TensorFlow: A Framework for Scalable Machine Learning' with Martin Wicke
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Title: TensorFlow: A Framework for Scalable Machine Learning
Date: October 19, 2016
Time: 12:00 PM ET
Duration: 1 hour, 3 minutes
Summary:
We introduce TensorFlow, a framework for scalable machine learning. Since its launch in 2015, TensorFlow has become a popular open-source project. In this Tutorial, we start from TensorFlow basics such as how to build and run Graphs, how to work with Sessions, Variables and Ops. We then show how to perform large-scale training using queues and distribute training on several devices or computers.
Presenter:
Martin Wicke is a software engineer working on Google's TensorFlow team. His main interest is making cutting edge machine learning infrastructure available to the world. After completing a PhD in computer graphics at ETH Zurich, Martin Wicke worked on simulation at Stanford University and UC Berkeley. Before joining Google, he worked at startups tackling problems in engineering, energy, robotics, and AI.
Date: October 19, 2016
Time: 12:00 PM ET
Duration: 1 hour, 3 minutes
Summary:
We introduce TensorFlow, a framework for scalable machine learning. Since its launch in 2015, TensorFlow has become a popular open-source project. In this Tutorial, we start from TensorFlow basics such as how to build and run Graphs, how to work with Sessions, Variables and Ops. We then show how to perform large-scale training using queues and distribute training on several devices or computers.
Presenter:
Martin Wicke is a software engineer working on Google's TensorFlow team. His main interest is making cutting edge machine learning infrastructure available to the world. After completing a PhD in computer graphics at ETH Zurich, Martin Wicke worked on simulation at Stanford University and UC Berkeley. Before joining Google, he worked at startups tackling problems in engineering, energy, robotics, and AI.
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