# Synapses

A **lightweight** library for **neural networks** that **runs anywhere**!

![Network Video](https://github.com/mrdimosthenis/Synapses/blob/master/network-video.gif?raw=true)

## [Getting Started](https://mrdimosthenis.github.io/Synapses)

### 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](https://mrdimosthenis.github.io/Synapses/?javascript)
* [Python](https://mrdimosthenis.github.io/Synapses/?python)
* [Java](https://mrdimosthenis.github.io/Synapses/?java)
* [C#](https://mrdimosthenis.github.io/Synapses/?csharp)
* [Scala](https://mrdimosthenis.github.io/Synapses/?scala)
* [F#](https://mrdimosthenis.github.io/Synapses/?fsharp)

#### It's compatible across languages

1. The [interface](https://github.com/mrdimosthenis/Synapses/blob/master/interface.md) 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](https://github.com/mrdimosthenis/Synapses/blob/master/network-drawing.png?raw=true)

#### 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](https://raw.githubusercontent.com/mrdimosthenis/Synapses/master/network.json) 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](https://github.com/mrdimosthenis/Synapses/tree/master/test-projects/remote-deps/JavaScriptTest/test)
* [Python](https://github.com/mrdimosthenis/Synapses/tree/master/test-projects/remote-deps/PythonTest/test)
* [Java](https://github.com/mrdimosthenis/Synapses/tree/master/test-projects/remote-deps/JavaTest/src/test/java)
* [C#](https://github.com/mrdimosthenis/Synapses/tree/master/test-projects/remote-deps/CSharpTest)
* [Scala](https://github.com/mrdimosthenis/Synapses/tree/master/test-projects/remote-deps/ScalaTest/src/test/scala)
* [F#](https://github.com/mrdimosthenis/Synapses/tree/master/test-projects/remote-deps/FSharpTest)

### Dependencies

* [circe](https://github.com/circe/circe)
* [FSharpx.Collections](https://github.com/fsprojects/FSharpx.Collections)
* [Newtonsoft.Json](https://github.com/JamesNK/Newtonsoft.Json)
* [PyFunctional](https://github.com/EntilZha/PyFunctional)

### Misc

![JetBrains](https://github.com/mrdimosthenis/Synapses/blob/master/jetbrains.png?raw=true)

[JetBrains tools have helped for this project!](https://www.jetbrains.com/?from=Synapses)


A lightweight library for neural networks that runs anywhere. 

Socket Acquires Coana to Bring Reachability Analysis to Every Appsec Team

synapses-py

A lightweight library for neural networks that runs anywhere

mrdimosthenis

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synapses-py

Synapses

Getting Started

Why Sypapses?

It's easy

It runs anywhere

It's compatible across languages

It offers visualizations

It's customizable

It's efficient

Data preprocessing is simple

Works for huge datasets

It's well tested

Dependencies

Misc

Keywords

Related posts

synapses-py

Synapses

Why Sypapses?

It's easy

It runs anywhere

It's compatible across languages

It offers visualizations

It's customizable

It's efficient

Data preprocessing is simple

Works for huge datasets

It's well tested

Dependencies

Misc

Keywords

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