ml.js
Machine learning and numerical analysis tools for Node.js and the Browser!
Pricing
Free tier
Flat rate
Adoption
↘CoolingLicense
Open Source
Data freshness
Aging · Jun 8, 2026Overview
What is ml.js?
ml.js provides a comprehensive set of machine learning algorithms and numerical methods for both server-side and client-side applications, making it easy to integrate advanced analytics into web projects.
Key differentiator
“ml.js stands out as a versatile library that supports both client-side and server-side machine learning, making it ideal for web developers who need to integrate advanced analytics directly into their applications.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
ml.js is not optimized for handling very large datasets, leading to slow execution times and high memory usage.
The official documentation lacks detailed explanations and practical examples, making it difficult for new users to understand how to use the library effectively.
The project has a small community, resulting in limited third-party contributions and slower response times for issues and feature requests.
Fit analysis
Who is it for?
✓ Best for
Web developers who need to integrate machine learning directly into their front-end applications
Node.js developers looking for a comprehensive set of numerical and statistical tools
Projects requiring both client-side and server-side machine learning capabilities
✕ Not a fit for
Teams needing real-time streaming analytics (ml.js is more suited for batch processing)
Large-scale distributed computing tasks that require specialized hardware or cloud services
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
Alternatives
Next step
Get Started with ml.js
Step-by-step setup guide with code examples and common gotchas.