ZeroML: A Next Generation AutoML Language
원문 초록
ZeroML is a new generation programming language for AutoML to drive the ML pipeline in a compiled and multi-paradigm way, with a pure functional core. Meeting the shortcomings introduced by Python, R, or Julia such as slow-running time, brittle pipelines or high dependency cost ZeroML brings the Microservices-based architecture adding the modular, reusable pieces such as DataCleaner, FeatureEngineer or ModelSelector. As a native multithread and memory-aware search optimized toolkit, and with one command deployability ability, ZeroML ensures non-coders and ML professionals to create high-accuracy models super fast and in a more reproducible way. The verbosity of the language ensures that when it comes to dropping into the backend, the code we will be creating is extremely clear but the level of repetition and boilerplate required when developing on the front end is now removed.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Overtuning in Hyperparameter Optimization
From Tiny Machine Learning to Tiny Deep Learning: A Survey
VirnyFlow: A Design Space for Responsible Model Development
OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization
MLZero: A Multi-Agent System for End-to-end Machine Learning Automation
When Your Own Output Becomes Your Training Data: Noise-to-Meaning Loops and a Formal RSI Trigger
토론
이 논문과 연결된 포럼 글이 아직 없습니다.