goml
Pure Go machine learning library for efficient model training and deployment.
Pricing
Free tier
Flat rate
Adoption
↘CoolingLicense
Open Source
Data freshness
Aging · Jun 8, 2026Overview
What is goml?
goml is a comprehensive machine learning library written entirely in Go. It provides developers with the tools necessary to train, evaluate, and deploy models without relying on external dependencies or languages.
Key differentiator
“goml stands out as a pure Go machine learning library, offering seamless integration into Go projects without the need for external dependencies or language interoperability issues.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
Small number of contributors on GitHub and limited activity in forums.
Does not support advanced algorithms such as gradient boosting or deep learning frameworks out-of-the-box.
Pure Go implementation might not leverage optimized native libraries like BLAS/LAPACK used in Python ML libraries.
Official documentation does not cover all features in detail, making it hard for new users to get started quickly.
Fit analysis
Who is it for?
✓ Best for
Developers building machine learning applications entirely within the Go ecosystem who need a pure Go solution.
Projects requiring efficient, lightweight machine learning models without external dependencies.
✕ Not a fit for
Teams that require extensive support for deep learning frameworks like TensorFlow or PyTorch.
Applications where performance is critical and highly optimized C/C++ libraries are preferred.
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Works well with
Next step
Get Started with goml
Step-by-step setup guide with code examples and common gotchas.