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ENorm vs TensorFlow: What are the differences?

What is ENorm? Equi-normalization of Neural Networks (by Facebook). A fast and iterative method for minimizing the L2 norm of the weights of a given neural network that provably converges to a unique solution.

What is TensorFlow? Open Source Software Library for Machine Intelligence. TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.

ENorm and TensorFlow can be primarily classified as "Machine Learning" tools.

ENorm is an open source tool with 104 GitHub stars and 8 GitHub forks. Here's a link to ENorm's open source repository on GitHub.

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Pros of ENorm
Pros of TensorFlow
    Be the first to leave a pro
    • 23
      High Performance
    • 16
      Connect Research and Production
    • 13
      Deep Flexibility
    • 9
      Auto-Differentiation
    • 9
      True Portability
    • 2
      Easy to use
    • 2
      High level abstraction
    • 1
      Powerful

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    Cons of ENorm
    Cons of TensorFlow
      Be the first to leave a con
      • 8
        Hard
      • 5
        Hard to debug
      • 1
        Documentation not very helpful

      Sign up to add or upvote consMake informed product decisions

      What is ENorm?

      A fast and iterative method for minimizing the L2 norm of the weights of a given neural network that provably converges to a unique solution.

      What is TensorFlow?

      TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.

      Need advice about which tool to choose?Ask the StackShare community!

      What companies use ENorm?
      What companies use TensorFlow?
      See which teams inside your own company are using ENorm or TensorFlow.
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      What tools integrate with ENorm?
      What tools integrate with TensorFlow?
        No integrations found

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        What are some alternatives to ENorm and TensorFlow?
        Keras
        Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
        PyTorch
        PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
        scikit-learn
        scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
        CUDA
        A parallel computing platform and application programming interface model,it enables developers to speed up compute-intensive applications by harnessing the power of GPUs for the parallelizable part of the computation.
        TensorFlow.js
        Use flexible and intuitive APIs to build and train models from scratch using the low-level JavaScript linear algebra library or the high-level layers API
        See all alternatives
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