[D] What useful personal projects have you made?

This page summarizes the projects mentioned and recommended in the original post on /r/MachineLearning
differential-equations Jax Deep Learning neural-differential-equations Machine Learning

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  • equinox

    Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/

    • A neural network library for JAX: Equinox. IMO the simplest/most-generic one out there.

  • diffrax

    Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/

    • Whilst this has been getting a bit of traction in the community, this started out life as a personal project. I needed a way to describe generic parameterised functions (not just neural networks) to be able to describe differential equation solvers, and found that existing options (Flax/Haiku) were overly-tailored to neural networks, and couldn't handle my use case.

  • 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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