AutoMLPipeline vs cnvrg.io

AutoMLPipeline vs cnvrg.io: What are the differences?

Developers describe AutoMLPipeline as "A package that makes it trivial to create and evaluate machine learning pipeline architectures (by IBM)". It is a package that makes it trivial to create complex ML pipeline structures using simple expressions. It leverages on the built-in macro programming features of Julia to symbolically process, manipulate pipeline expressions, and automatically discover optimal structures for machine learning prediction and classification. On the other hand, cnvrg.io is detailed as "An end-to-end machine learning platform to build and deploy AI models at scale". It is an AI OS, transforming the way enterprises manage, scale and accelerate AI and data science development from research to production. The code-first platform is built by data scientists, for data scientists and offers unrivaled flexibility to run on-premise or cloud.

AutoMLPipeline and cnvrg.io can be primarily classified as "Machine Learning" tools.

Some of the features offered by AutoMLPipeline are:

• Pipeline API that allows high-level description of processing workflow
• Common API wrappers for ML libs including Scikitlearn, DecisionTree, etc
• Symbolic pipeline parsing for easy expression of complexed pipeline structures

On the other hand, cnvrg.io provides the following key features:

• Machine Learning Pipelines
• AI Library
• Open Compute

AutoMLPipeline is an open source tool with 185 GitHub stars and 18 GitHub forks. Here's a link to AutoMLPipeline's open source repository on GitHub.