FEDOT

AutoML framework for composite modeling pipelines

EstablishedOpen SourceLow lock-in

Pricing

See website

Flat rate

Adoption

Stable

License

Open Source

Data freshness

Overview

What is FEDOT?

FEDOT is an AutoML framework that automates the design of composite modeling pipelines. It supports classification, regression, and time series forecasting tasks on various types of data.

Key differentiator

FEDOT stands out by providing an automated approach to designing composite modeling pipelines, particularly excelling in handling multi-modal datasets and time series forecasting.

Capability profile

Strength Radar

Automated design…Support for clas…Handling of mult…

Honest assessment

Strengths & Weaknesses

↑ Strengths

Automated design of composite modeling pipelines

Support for classification, regression, and time series forecasting tasks

Handling of multi-modal datasets

Fit analysis

Who is it for?

✓ Best for

Teams needing automated pipeline design for time series forecasting

Projects requiring handling of multi-modal datasets without extensive manual tuning

Developers looking to reduce the complexity in setting up machine learning pipelines

✕ Not a fit for

Real-time applications where immediate model updates are critical

Scenarios with extremely limited computational resources, as FEDOT may require significant processing power for automation

Cost structure

Pricing

Free Tier

None

Starts at

See website

Model

Flat rate

Enterprise

None

Performance benchmarks

How Fast Is It?

Ecosystem

Relationships

Alternatives

Next step

Get Started with FEDOT

Step-by-step setup guide with code examples and common gotchas.

View Setup Guide →