julia-ann

3.3
(3)

julia-ann is the implementation of backpropagation artificial neural networks in Julia that allow users to build multilayer networks and accept DataFrames as inputs. fit! and predict currently require Float64 matrices and vectors.

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Showing 3 julia-ann reviews
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Aaron A.
Validated Reviewer
Review Source
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"Mediocre Neural Network Gateway"

What do you like best?

The ability to create multi layered networks and advocate for these on behalf of the neural systems in play.

What do you dislike?

The backlogged entry can take quite awhile to synthesize as well as the framework is slightly outdated compared to more modern stacking and layered data programs.

Recommendations to others considering the product:

Consider your options!

What problems are you solving with the product? What benefits have you realized?

None so far but we hope to solve more in the future with this product or a similar one.

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Kyle P.
Validated Reviewer
Review Source
content

"A good implementation of a neural network."

What do you like best?

The program is very easy to implement into an existing Java project.

What do you dislike?

Some of the code is poorly commented or could be laid out better

What problems are you solving with the product? What benefits have you realized?

An easy way to implement a neural network in Julia.

What Artificial Neural Network solution do you use?

Thanks for letting us know!
GM
G2 User in Medical Devices
Validated Reviewer
Review Source
content

"julia ann review"

What do you like best?

she was great in the interactive session capabilities

What do you dislike?

it was not very user friendly. i feel that it should be more intuitive

What problems are you solving with the product? What benefits have you realized?

solves communication problems and cuts down time

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