igel

What it is

Igel is a delightful machine learning tool that allows users to train, test, and utilize models without the need for coding. It simplifies the process of working with machine learning for those who may not have extensive programming experience.

Igel stands out as a no-code solution, making it unique in its approach to simplifying machine learning tasks for users without programming experience.

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 language support beyond Python

   Primary development and API are centered around Python, with no official support for other languages.

2. 02

   Complex setup process for new users

   Documentation lacks step-by-step guides for setting up the environment from scratch.

3. 03

   Performance issues with large datasets

   Known performance bottlenecks when processing datasets larger than 1GB.

4. 04

   Small and less active community

   Low number of contributors on the GitHub repository and limited activity in forums or Q&A sites.

What it does well

• No-code machine learning model training and testing.

• Simplified process for utilizing models without programming knowledge.

• Open-source with MIT license.

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.