内容简介：AYou are all set!Supported languages:
Synapses
A lightweight library for neural networks that runs anywhere .
Getting Started
Why Sypapses?
It's easy
- Add one dependency to your project.
- Write a single import statement .
- Use a few pure functions .
You are all set!
Supported languages:
It's compatible across languages
- The interface is common across languages.
- 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.
Dependencies
1 : Your Honour should be aware that I mean almost anywhere.
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