ZeroML用函数式语言重构AutoML，让模型开发更快更可复现。
ZeroML: A Next Generation AutoML Language
- 基于微服务架构的函数式编程语言，模块化设计提升可复用性。
- 一键部署支持多线程与内存优化，加速模型搜索过程。
- 适合非编码者与专业人员，减少重复代码，提高开发效率。
ZeroML 是一种新一代 AutoML 编程语言，以纯函数式核心实现编译型、多范式建模流程。针对 Python、R、Julia 等语言存在的运行慢、管道脆弱、依赖成本高等问题，引入微服务架构，提供 DataCleaner、FeatureEngineer、ModelSelector 等可复用模块。作为原生多线程、内存感知的搜索优化工具包，支持单命令部署，使非编码者与机器学习从业者能快速构建高精度模型，且过程更具可复现性。语言的冗余设计确保后端代码清晰，前端开发则自动消除重复和样板代码。
原文摘要 · Abstract (English)
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.
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