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synapses

WebJar for synapses

License

License

MIT
GroupId

GroupId

org.webjars.npm
ArtifactId

ArtifactId

synapses
Last Version

Last Version

7.1.0
Release Date

Release Date
Type

Type

jar
Description

Description

synapses
WebJar for synapses
Project URL

Project URL

https://www.webjars.org
Source Code Management

Source Code Management

https://github.com/mrdimosthenis/Synapses

Download synapses

Filename Size
synapses-7.1.0.pom
synapses-7.1.0.jar 110 KB
synapses-7.1.0-sources.jar 22 bytes
synapses-7.1.0-javadoc.jar 22 bytes
Browse

How to add to project

<!-- https://jarcasting.com/artifacts/org.webjars.npm/synapses/ -->
<dependency>
    <groupId>org.webjars.npm</groupId>
    <artifactId>synapses</artifactId>
    <version>7.1.0</version>
</dependency>
// https://jarcasting.com/artifacts/org.webjars.npm/synapses/
implementation 'org.webjars.npm:synapses:7.1.0'
// https://jarcasting.com/artifacts/org.webjars.npm/synapses/
implementation ("org.webjars.npm:synapses:7.1.0")
'org.webjars.npm:synapses:jar:7.1.0'
<dependency org="org.webjars.npm" name="synapses" rev="7.1.0">
  <artifact name="synapses" type="jar" />
</dependency>
@Grapes(
@Grab(group='org.webjars.npm', module='synapses', version='7.1.0')
)
libraryDependencies += "org.webjars.npm" % "synapses" % "7.1.0"
[org.webjars.npm/synapses "7.1.0"]

Dependencies

There are no dependencies for this project. It is a standalone project that does not depend on any other jars.

Project Modules

There are no modules declared in this project.

Synapses

A lightweight library for neural networks that runs anywhere!

Network Video

Getting Started

Why Sypapses?

It's easy

  1. Add one dependency to your project.
  2. Write a single import statement.
  3. Use a few pure functions.

You are all set!

It runs anywhere

Supported languages:

It's compatible across languages

  1. The interface is common across languages.
  2. You can transfer a network from one platform to another via its json instance. Create a neural network in Python, train it in Java and get its predictions in JavaScript!

It offers visualizations

Get an overview of a neural network by taking a brief look at its svg drawing.

Network Drawing

It's customizable

You can specify the activation function and the weight distribution for the neurons of each layer. If this is not enough, edit the json instance of a network to be exactly what you have in mind.

It's efficient

The implementation is based on lazy list. The information flows smoothly. Everything is obtained at a single pass.

Data preprocessing is simple

By annotating the discrete and continuous attributes, you can create a preprocessor that encodes and decodes the datapoints.

Works for huge datasets

The functions that process big volumes of data, have an Iterable/Stream as argument. RAM should not get full!

It's well tested

Every function is tested for every language. Please take a look at the test projects.

Dependencies

Misc

JetBrains

JetBrains tools have helped for this project!

Versions

Version
7.1.0