Go , an open source language by Google was initially created by  group of engineers who were frustrated with C++. Ever since their creation, the language has gotten traction for its simplicity. It ranked highly in the programming popularity indexes of Redmonk & TiOBE.

Some of the companies & use cases for Go Include:

• Google, for many projects, notably including download server dl.google.com

• Dropbox, migrated some of their critical components from Python to Go

• CloudFlare, for their delta-coding proxy Railgun, their distributed DNS service, as well as tools for cryptography, logging, stream processing, and accessing SPDY sites

• SoundCloud, for "dozens of systems"

• The BBC, in some games and internal projects

• Novartis, for an internal inventory system

• Splice, for the entire backend (API and parsers) of their online music collaboration platform

• Cloud Foundry, a platform as a service

• CoreOS, a Linux-based operating system that utilizes Docker containers

• MongoDB, tools for administrating MongoDB instances

• Zerodha, for realtime peering and streaming of market data

• Chango, a programmatic advertising company uses Go in its real-time bidding systems.

• SendGrid, a Boulder, Colorado-based transactional email delivery and management service.[

• Plug.dj, an interactive online social music streaming website.

Once a programming language starts to get traction, analytics libraries are not far behind.  We have collected a list of Machine Libraries in Go Language for people interested in experimenting with Go or already familiar with Go.

1. Generalized Machine Learning Libraries:

   1. GoML - https://github.com/cdipaolo/goml

   2. Machine Learning libraries for Go Lang : https://github.com/alonsovidales/go_ml:

   3. MLGo - https://code.google.com/p/mlgo/

   4. GoLearn:

2. Neural Networks

   1. Neural Networks written in go : https://github.com/goml/gobrain

   2. Go Fann - https://github.com/white-pony/go-fann

   3. Multi-Layer Perceptron Neural Network - https://github.com/schuyler/neural-go -

   4. Genetic Algorithms library written in Go / golang - https://github.com/thoj/go-galib

3. Linear Algebra:

   1. Linear Algebra for Go & Matrix Library:

   2. Mat64: Package mat64 provides basic linear algebra operations for float64 matrices.

   3. BLAS Implementation for Go

   4. https://github.com/danieldk/golinear - liblinear bindings for Go

4. Probability Distribution Functions

   1. http://godoc.org/code.google.com/p/probab

   2. https://github.com/e-dard/godist

5. Decision Trees:

   1. Hector https://github.com/xlvector/hector

   2. Decision Trees in Go - https://github.com/ajtulloch/decisiontrees

   3. CloudForest - https://github.com/ryanbressler/CloudForest -

6. Bayesian Classifiers:

   1. https://github.com/jbrukh/bayesian - Perform naive Bayesian classification

   2. https://github.com/eaigner/shield - Bayesian text classifier

7. Recommendation Engines in Go

   1. Collaborative Filtering (CF) Algorithms in Go - https://github.com/timkaye11/goRecommend

   2. Recommendation engine for Go - https://github.com/muesli/regommend

A more detailed compilation is available on Fodop