Machine Learning Libraries in Go Language



Go, an open-source language by Google was initially created by a 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.
  • 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:
    2. Machine Learning libraries for Go Lang : https://github.com/alonsovidales/go_ml:
  2. Neural Networks
    1. Neural Networks wrote in go: https://github.com/goml/gobrain
    3. Multi-Layer Perceptron Neural Network - https://github.com/schuyler/neural-go -
    4. Genetic Algorithms library is written in Go / golang - https://github.com/thoj/go-galib
  3. Linear Algebra:
    2. Mat64: Package mat64 provides basic linear algebra operations for float64 matrices.
    4. https://github.com/danieldk/golinear - liblinear bindings for Go
  4. Probability Distribution Functions
  5. Decision Trees:
  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
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