# My own Feedforward Neural Network library :-)

**URL:** <https://discourse.julialang.org/t/my-own-feedforward-neural-network-library/37198>\
**Category:** Machine Learning\
**Created:** [April 7, 2020, 10:15pm UTC](https://discourse.julialang.org/t/my-own-feedforward-neural-network-library/37198 "2020-04-07T22:15:58Z")\
**Posts on this page:** 1\
**Showing post:** 18

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**Author:** ![sylvaticus](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/sylvaticus/32/203883_2.png) [@sylvaticus](https://discourse.julialang.org/u/sylvaticus)\
**Post date:** [June 9, 2020, 10:19am UTC](https://discourse.julialang.org/t/my-own-feedforward-neural-network-library/37198/18 "2020-06-09T10:19:02Z")

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> [@kevbonham](#):
>
> Cool! Now toss it into a package, write some tests, and get it registered

> [@\[ANN\] BetaML.jl.. yet an other (simple) Machine Learning Package](https://discourse.julialang.org/t/ann-betaml-jl-yet-an-other-simple-machine-learning-package/41057):
>
> [BetaML\_logo] [microExample\_white] Dear all, I would like to announce the availability of “[BetaML](https://github.com/sylvaticus/BetaML.jl)” , the Beta Machine Learning toolkit, a package for Machine Learning algorithms and related utilities. The toolkit is currently made of 4 modules. Perceptron includes the classical perceptron linear classifier, but also the non-linear kernel perceptron and the gradient-based Pegasus classifier. Nn implements easy-to-model Artificial Neural Networks (simple feed-forward only for the moment, but w…

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