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Google AutoML Tables

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Google AutoML Tables vs Swift AI: What are the differences?

Google AutoML Tables: Automatically build and deploy machine learning models on structured data. Enables your entire team of data scientists, analysts, and developers to automatically build and deploy machine learning models on structured data at massively increased speed and scale; Swift AI: A.I. and machine learning library written in Swift. Swift AI is a high-performance AI and machine learning library written entirely in Swift. We currently support iOS and OS X, with support for more platforms coming soon!.

Google AutoML Tables and Swift AI can be categorized as "Machine Learning" tools.

Swift AI is an open source tool with 5.58K GitHub stars and 542 GitHub forks. Here's a link to Swift AI's open source repository on GitHub.

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- No public GitHub repository available -

What is Google AutoML Tables?

Enables your entire team of data scientists, analysts, and developers to automatically build and deploy machine learning models on structured data at massively increased speed and scale.

What is Swift AI?

Swift AI is a high-performance AI and machine learning library written entirely in Swift. We currently support iOS and OS X, with support for more platforms coming soon!

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Jobs that mention Google AutoML Tables and Swift AI as a desired skillset
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San Francisco, CA, US; Palo Alto, CA, US; Seattle, WA, US
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San Francisco, CA, US; Palo Alto, CA, US; Seattle, WA, US
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    What tools integrate with Google AutoML Tables?
    What tools integrate with Swift AI?
    What are some alternatives to Google AutoML Tables and Swift AI?
    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.
    Keras
    Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
    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.
    See all alternatives