ZeroML: A Next Generation AutoML Language

TL;DR

ZeroML introduces a new functional programming language designed for AutoML, enabling fast, modular, and reproducible ML pipeline development with a microservices architecture and native multithreading.

Contribution

It presents ZeroML, a novel AutoML language that overcomes Python, R, and Julia limitations through a compiled, multi-paradigm, microservices-based approach with optimized search and deployment features.

Findings

Supports high-accuracy models creation rapidly

Ensures reproducibility and modularity in ML pipelines

Offers native multithreading and deployment capabilities

Abstract

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.