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ScalaNLP

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TensorFlow.js

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ScalaNLP vs TensorFlow.js: What are the differences?

What is ScalaNLP? A suite of machine learning and numerical computing libraries. ScalaNLP is a suite of machine learning and numerical computing libraries.

What is TensorFlow.js? Machine Learning in JavaScript. 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.

ScalaNLP and TensorFlow.js can be categorized as "Machine Learning" tools.

ScalaNLP and TensorFlow.js are both open source tools. It seems that TensorFlow.js with 11.2K GitHub stars and 816 forks on GitHub has more adoption than ScalaNLP with 2.91K GitHub stars and 674 GitHub forks.

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Pros of ScalaNLP
Pros of TensorFlow.js
    Be the first to leave a pro
    • 5
      Open Source
    • 5
      NodeJS Powered
    • 2
      Deploy python ML model directly into javascript
    • 1
      Privacy - no data sent to server
    • 1
      Can run TFJS on backend, frontend, react native, + IOT
    • 1
      Runs Client Side on device
    • 1
      Easy to share and use - get more eyes on your research
    • 1
      Cost - no server needed for inference

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    What is ScalaNLP?

    ScalaNLP is a suite of machine learning and numerical computing libraries.

    What is 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

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

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      What tools integrate with ScalaNLP?
      What tools integrate with TensorFlow.js?
      What are some alternatives to ScalaNLP and TensorFlow.js?
      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.
      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.
      Keras
      Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
      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.
      See all alternatives