go-ml
A Go library implementing essential machine learning algorithms including linear regression, logistic regression, and neural networks.
What is go-ml?
go_ml is a Go library that implements essential machine learning algorithms for data mining and analysis. It provides implementations of linear regression, logistic regression, neural networks, collaborative filtering, and Gaussian multivariate distribution for anomaly detection. The library includes optimization functions to calculate optimal parameter configurations for minimizing cost values across all algorithms.
Go developers who need to incorporate machine learning capabilities into their applications without relying on external Python or R dependencies, particularly those working on data analysis, predictive modeling, or recommendation systems.
Developers choose go_ml for its native Go implementation of core ML algorithms, allowing them to maintain a consistent Go codebase without language interoperability overhead. The library provides a focused collection of well-established algorithms with optimization functions specifically designed for the Go ecosystem.
Overview
Machine Learning libraries for Go Lang - Linear regression, Logistic regression, etc.
Use Cases
Best For
- Adding linear regression models to Go applications
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