What Apple hardware do I need for CUDA-based deep learning tasks?

This page summarizes the projects mentioned and recommended in the original post on /r/macbook
Machine Learning HacktoberFest julia-language Flux Julia

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  • Metal.jl

    Metal programming in Julia

    • If you are really committed to running on Apple hardware then take a look at Tensorflow for macOS. Another option is the Julia programming language which has very basic Metal support at a CUDA-like level. FluxML would be the ML framework in Julia. I’m not sure either option will be painless or let you do everything you could do with a Nvidia GPU.

  • Flux.jl

    Relax! Flux is the ML library that doesn't make you tensor

    • If you are really committed to running on Apple hardware then take a look at Tensorflow for macOS. Another option is the Julia programming language which has very basic Metal support at a CUDA-like level. FluxML would be the ML framework in Julia. I’m not sure either option will be painless or let you do everything you could do with a Nvidia GPU.

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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  • julia

    The Julia Programming Language

    • If you are really committed to running on Apple hardware then take a look at Tensorflow for macOS. Another option is the Julia programming language which has very basic Metal support at a CUDA-like level. FluxML would be the ML framework in Julia. I’m not sure either option will be painless or let you do everything you could do with a Nvidia GPU.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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