Top 7 Golang Machine Learning Libraries To Use In 2021

Go is a popular open-source programming language created by google researchers. It has many attractive features like garbage collector, cross-platform, efficient concurrency and so on. Machine learning helped everyone( including non-CS people too) over the past few years. We know that Go provides faster speeds at accessing requests over the internet, and also it can be used for something practical- like Machine learning. Here we’ve listed out some top machine learning libraries in Golang. Let’s see which are those.

You can know the reasons to use golang at- Why Golang Is Better Than Other Languages?

Golang Machine Learning Libraries-
1. Gorgonia-
This library helps in facilitating machine learning completely in Go language. Main goal of this library is to be a highly performant machine learning and graph computation-based library that can scale across multiple machines. Also, it provides a platform for the exploration of non-standard deep learning and neural network related research. It can perform processes like neo-Hebbian learning, corner-cutting calculations, etc. Some of its features are-

Gorgonia can perform automatic differentiation, symbolic differentiation, gradient descent optimization and numerical stabilisation.
Library provides various convenience functions to help create neural networks.
This library supports CUDA and GPGPU computation.
2. Golea
-
It is a popular library in Go language and known as the ‘batteries included’ machine learning library for Go. Golea
aims to contribute simplicity paired with customizability. It has great features like-

Data are loaded in as Instances. You can then perform matrix like operations on them, and pass them to estimators.
This library is like popular Scikit-lea
library in Python because it implements the Scikit-lea
interface of Fit/Predict.
Golea
includes helper functions for data such as train splitting, test splitting and cross-validation.
3. Goml-
It is a machine learning library written in Golang that allows developers to include machine learning into their apps. Goml includes many models that lets you to learn in an online, reactive manner by data transfer to streams held on channels. Those models include traditional, batch learning interfaces etc. Library includes extensive documentation, comprehensive tests, and expressive, clean, modular source code. Community contribution is heavily encouraged. All code of Goml is well documented and the source is readable if you’d like to make sense of it all.

Know more at- https://solaceinfotech.com/blog/top-7-golang-machine-learning-libraries-to-use-in-2021/