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README.md

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# Optimisers.jl
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[![][docs-stable-img]][docs-stable-url]
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<!-- [![][docs-stable-img]][docs-stable-url] -->
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[![][docs-dev-img]][docs-dev-url]
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[![][action-img]][action-url]
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[![][coverage-img]][coverage-url]
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[coverage-img]: https://codecov.io/gh/FluxML/Optimisers.jl/branch/master/graph/badge.svg
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[coverage-url]: https://codecov.io/gh/FluxML/Optimisers.jl
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Optimisers.jl defines many standard optimisers and utilities for learning loops.
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Optimisers.jl defines many standard gradient-based optimisation rules, and tools for applying them to deeply nested models.
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The API for defining an optimiser, and using it is simple.
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This is the future of training for [Flux.jl](https://github.com/FluxML/Flux.jl) neural networks,
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but it can be used separately on anything understood by [Functors.jl](https://github.com/FluxML/Functors.jl).
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## Installation
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