Aerosolve vs scikit-learn: What are the differences?
Developers describe Aerosolve as "A machine learning package built for humans (created by Airbnb)". This library is meant to be used with sparse, interpretable features such as those that commonly occur in search (search keywords, filters) or pricing (number of rooms, location, price). It is not as interpretable with problems with very dense non-human interpretable features such as raw pixels or audio samples. On the other hand, scikit-learn is detailed as "Easy-to-use and general-purpose machine learning in Python". scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
Aerosolve and scikit-learn can be primarily classified as "Machine Learning" tools.
Aerosolve and scikit-learn are both open source tools. scikit-learn with 36K GitHub stars and 17.6K forks on GitHub appears to be more popular than Aerosolve with 4.58K GitHub stars and 578 GitHub forks.
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What is Aerosolve?
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