Recommendations for Books on Deep Learning.

This page summarizes the projects mentioned and recommended in the original post on /r/swift
Machine Learning Deep Learning deep-neural-networks gradient-descent automatic-differentiation

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  • DL4S

    Accelerated tensor operations and dynamic neural networks based on reverse mode automatic differentiation for every device that can run Swift - from watchOS to Linux

    • If you want to go the latter route, Apple provides a bunch of low level frameworks for this: Accelerate, BNNS, ML Compute and MetalPerformanceShaderGraph. CoreML also supports some limited fine tuning capabilities. There are also 3rd party solutions, like DL4S (which I created).

  • 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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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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