Synapses

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!

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'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

1 : Your Honour should be aware that I mean almost anywhere.