December 2018
Beginner to intermediate
490 pages
10h 38m
English
Content preview from Data Analysis with PythonBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Getting started with TensorFlow
There are multiple open source deep learning frameworks besides TensorFlow (https://www.tensorflow.org) that I could have chosen for this sample application.
Some of the most popular frameworks are as follows:
- PyTorch (http://pytorch.org)
- Caffee2 (https://caffe2.ai)
- MXNet (https://mxnet.apache.org)
- Keras (https://keras.io): A high-level neural network abstraction API capable of running other deep learning frameworks such as TensorFlow, CNTK (https://github.com/Microsoft/cntk), and Theano (https://github.com/Theano/Theano)
TensorFlow APIs are available in multiple languages: Python, C++, Java, Go, and, more recently, JavaScript. We can distinguish two categories of APIs: high level and low level, represented by this diagram: ...
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