November 2018
Intermediate to advanced
322 pages
7h 54m
English
Content preview from TensorFlow Machine Learning Projects
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Summary
In this chapter, we briefly covered the TensorFlow library. We covered the TensorFlow data model elements, such as constants, variables, and placeholders, and how they can be used to build TensorFlow computation graphs. We learned how to create tensors from Python objects. Tensor objects can also be generated as specific values, sequences, or random valued distributions from various TensorFlow library functions.
We covered the TensorFlow programming model, which includes defining and executing computation graphs. These computation graphs have nodes and edges. The nodes represent operations and edges represent tensors that transfer data from one node to another. We covered how to create and execute graphs, the order of execution, ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.