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Machine Learning library for Rust
Apache MXNet is a deep learning framework and distributed machine learning library designed for training and deploying neural networks across distributed systems, mobile devices, and hardware accelerators. It functions as a cross-platform runtime and a dynamic dataflow scheduler that optimizes neural network execution. The framework provides a multi-language API, enabling the development of machine learning models using Python, R, Julia, Scala, Go, and JavaScript. It supports high-performance model training and the scaling of workloads across multiple GPUs and machines. The system covers cap
An Open-Source Machine Learning Framework in Rust Δ
The main features of delta-rs/delta are: Machine Learning Frameworks.
Projects with overlapping indexed features include: asafschers/scoruby — Ruby Scoring API for PMML. athemathmo/rusty-machine — Machine Learning library for Rust. avinashshenoy97/rusticsom — Rust library for Self Organising Maps (SOM). cardmagic/classifier — A general classifier module to allow Bayesian and LSI classifications. catboost/catboost — CatBoost is a gradient boosting machine learning library used to train decision tree ensembles for regression,… apache/incubator-mxnet — Apache MXNet is a deep learning framework and distributed machine learning library designed for training and deploying…
