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Differentiable Programming

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Deep Learning with Swift for TensorFlow
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Abstract

In this chapter, we start by inspiring you to adopt the Swift language for deep learning by comparing (Section 3.1) its powerful capabilities to the Python language. We also introduce an extended language called “Swift for TensorFlow” (Section 3.2) for general-purpose programming and for learning, practicing, and researching the machine learning field. Because Python is currently used heavily for numerical computation, we show how Swift for TensorFlow can easily access (Section 3.4) Python’s built-ins, libraries, and user-defined entities. Finally, we close this chapter with a summary (Section 3.5).

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Notes

  1. 1.

    GIL stands for “Global Interpreter Lock.”

  2. 2.

    https://developer.apple.com/xcode/swiftui/

  3. 3.

    https://vapor.codes

  4. 4.

    https://swift.org/blog/aws-lambda-runtime/

  5. 5.

    https://github.com/HIPS/autograd

  6. 6.

    https://pytorch.org/

  7. 7.

    https://tensorflow.org/

  8. 8.

    https://keras.io

  9. 9.

    www.deeplearning.net/software/theano/

  10. 10.

    https://docs.swift.org/swift-book/

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© 2021 Rahul Bhalley

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Bhalley, R. (2021). Differentiable Programming. In: Deep Learning with Swift for TensorFlow. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-6330-3_3

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