synapses

License	MIT
GroupId	com.github.mrdimosthenis
ArtifactId	synapses_2.13
Last Version	7.3.1
Release Date	Apr 12, 2020
Type	jar
Description	synapses synapses
Project URL	https://github.com/mrdimosthenis/Synapses
Project Organization	com.github.mrdimosthenis
Source Code Management	https://github.com/mrdimosthenis/Synapses

Download synapses_2.13

Filename	Size
synapses_2.13-7.3.1.pom
synapses_2.13-7.3.1.jar	158 KB
synapses_2.13-7.3.1-sources.jar	11 KB
synapses_2.13-7.3.1-javadoc.jar	1 MB

How to add to project

Apache Maven

<!-- https://jarcasting.com/artifacts/com.github.mrdimosthenis/synapses_2.13/ -->
<dependency>
    <groupId>com.github.mrdimosthenis</groupId>
    <artifactId>synapses_2.13</artifactId>
    <version>7.3.1</version>
</dependency>

Gradle Groovy

// https://jarcasting.com/artifacts/com.github.mrdimosthenis/synapses_2.13/
implementation 'com.github.mrdimosthenis:synapses_2.13:7.3.1'

Gradle Kotlin

// https://jarcasting.com/artifacts/com.github.mrdimosthenis/synapses_2.13/
implementation ("com.github.mrdimosthenis:synapses_2.13:7.3.1")

Apache Buildr

'com.github.mrdimosthenis:synapses_2.13:jar:7.3.1'

Apache Ivy

<dependency org="com.github.mrdimosthenis" name="synapses_2.13" rev="7.3.1">
  <artifact name="synapses_2.13" type="jar" />
</dependency>

Groovy Grape

@Grapes(
@Grab(group='com.github.mrdimosthenis', module='synapses_2.13', version='7.3.1')
)

Scala SBT

libraryDependencies += "com.github.mrdimosthenis" % "synapses_2.13" % "7.3.1"

Leiningen

[com.github.mrdimosthenis/synapses_2.13 "7.3.1"]

Dependencies

compile (4)

Group / Artifact	Type	Version
org.scala-lang : scala-library	jar	2.13.1
io.circe : circe-core_2.13	jar	0.12.3
io.circe : circe-generic_2.13	jar	0.12.3
io.circe : circe-parser_2.13	jar	0.12.3

Project Modules

There are no modules declared in this project.

Synapses

A lightweight library for neural networks that runs anywhere!

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:

• JavaScript
• Python
• Java
• C#
• Scala
• F#

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.

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.

• JavaScript
• Python
• Java
• C#
• Scala
• F#

Dependencies

• circe
• FSharpx.Collections
• FSharp.SystemTextJson
• PyFunctional

Misc

JetBrains tools have helped for this project!

Versions

Version
7.3.1 Apr 12, 2020
7.3.0 Mar 8, 2020
7.2.1 Feb 3, 2020
7.2.0 Feb 2, 2020
7.2.0.rc1 Feb 2, 2020
7.1.1 Jan 12, 2020
7.1.0 Jan 12, 2020
6.0.0 Jan 12, 2020