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Numba

10
32
+ 1
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Swift AI

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+ 1
0
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Swift AI vs Numba: What are the differences?

Developers describe Swift AI as "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!. On the other hand, Numba is detailed as "An open source JIT compiler that translates a subset of Python and NumPy code into fast machine code". It translates Python functions to optimized machine code at runtime using the industry-standard LLVM compiler library. It offers a range of options for parallelising Python code for CPUs and GPUs, often with only minor code changes.

Swift AI and Numba can be primarily classified as "Machine Learning" tools.

Swift AI is an open source tool with 5.61K GitHub stars and 546 GitHub forks. Here's a link to Swift AI's open source repository on GitHub.

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What is Numba?

It translates Python functions to optimized machine code at runtime using the industry-standard LLVM compiler library. It offers a range of options for parallelising Python code for CPUs and GPUs, often with only minor code changes.

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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    What are some alternatives to Numba and Swift AI?
    Julia
    Julia is a high-level, high-performance dynamic programming language for technical computing, with syntax that is familiar to users of other technical computing environments. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library.
    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.
    NumPy
    Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.
    PyPy
    It is a very compliant implementation of the Python language, featuring a JIT compiler. It runs code about 7 times faster than CPython.
    Pandas
    Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more.
    See all alternatives