scikit-learn VS Robot Framework

Compare scikit-learn vs Robot Framework and see what are their differences.


scikit-learn: machine learning in Python (by scikit-learn)

Robot Framework

Generic automation framework for acceptance testing and RPA (by robotframework)
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scikit-learn Robot Framework
24 9
48,142 6,477
0.8% 1.1%
9.9 9.6
1 day ago 7 days ago
Python Python
BSD 3-clause "New" or "Revised" License Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.


Posts with mentions or reviews of scikit-learn. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-11-13.

Robot Framework

Posts with mentions or reviews of Robot Framework. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-11-14.

What are some alternatives?

When comparing scikit-learn and Robot Framework you can also consider the following projects:

pytest - The pytest framework makes it easy to write small tests, yet scales to support complex functional testing

Keras - Deep Learning for humans

Surprise - A Python scikit for building and analyzing recommender systems

Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

tensorflow - An Open Source Machine Learning Framework for Everyone

gensim - Topic Modelling for Humans

Behave - BDD, Python style.


Selenium Wire - Extends Selenium's Python bindings to give you the ability to inspect requests made by the browser.

hypothesis - Hypothesis is a powerful, flexible, and easy to use library for property-based testing.

Slash - The Slash testing infrastructure

TFLearn - Deep learning library featuring a higher-level API for TensorFlow.