The TensorFlow library provides for the use of computational graphs, with automatic parallelization across resources. This architecture is ideal for implementing neural networks. Robert Schroll offers an overview of TensorFlow’s capabilities in Python, demonstrating how to build machine learning algorithms piece by piece and how to use TensorFlow’s Keras API with several hands-on applications.
Robert Schroll is a data scientist in residence at the Data Incubator. Previously, he held postdocs in Amherst, Massachusetts, and Santiago, Chile, where he realized that his favorite parts of his job were teaching and analyzing data. He made the switch to data science and has been at the Data Incubator since. Robert holds a PhD in physics from the University of Chicago.
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