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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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