EvalML

What it is

EvalML is a library that automates the process of building, optimizing, and evaluating machine learning pipelines using domain-specific functions. It simplifies the development of complex ML models by handling many aspects automatically.

EvalML stands out by offering automated pipeline creation and optimization with domain-specific functions, making it easier to develop complex ML models without extensive manual tuning.

When it fits — and when it doesn’t

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

1. 01

   Limited integrations with non-Python data sources and tools

   Primary focus on Python ecosystem limits compatibility with other languages and frameworks

2. 02

   Performance issues with large datasets

   EvalML's automated pipeline creation can be slow when processing very large datasets, impacting real-time or near-real-time applications

What it does well

• Automated pipeline creation and optimization

• Domain-specific functions for ML tasks

• Evaluation of pipelines with various metrics

Pricing

Free tier

YesOpen source — free to use

Paid from

$0

Model

Flat rate

Enterprise plan

No

Pricing not independently confirmed — check the vendor’s page.