LAML is a stand-alone pure Java library for linear algebra and machine learning. The goal is to build efficient and easy-to-use linear algebra and machine learning libraries. The reason why linear algebra and machine learning are built together is that full control of the basic data structures for matrices and vectors is required to have fast implementation for machine learning methods. Additionally, LAML provides a lot of commonly used matrix functions in the same signature to MATLAB, thus can also be used to manually convert MATLAB code to Java code.

Features

  • Stand-alone Java library, completely cross-platform
  • Built-in Linear Algebra (LA) library
  • Full control of matrices and vectors
  • Many general-purpose optimization algorithms
  • Fast implementation of Machine Learning (ML) methods
  • Matrix functions with almost the same signature to MATLAB
  • Well documented source code and friendly API, very easy to use

Project Activity

See All Activity >

Categories

Machine Learning

Follow LAML:Linear Algebra and Machine Learning

LAML:Linear Algebra and Machine Learning Web Site

Other Useful Business Software
Go From AI Idea to AI App Fast Icon
Go From AI Idea to AI App Fast

One platform to build, fine-tune, and deploy ML models. No MLOps team required.

Access Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
Try Free
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of LAML:Linear Algebra and Machine Learning!

Additional Project Details

Programming Language

Java

Related Categories

Java Machine Learning Software

Registered

2013-12-18