Aerosolve vs Streamlit

Aerosolve vs Streamlit: What are the differences?

What is Aerosolve? 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.

What is Streamlit? A Python app framework built specifically for Machine Learning and Data Science teams. It is the app framework specifically for Machine Learning and Data Science teams. You can rapidly build the tools you need. Build apps in a dozen lines of Python with a simple API.

Aerosolve and Streamlit can be primarily classified as "Machine Learning" tools.

Some of the features offered by Aerosolve are:

• A thrift based feature representation that enables pairwise ranking loss and single context multiple item representation.
• A feature transform language gives the user a lot of control over the features
• Human friendly debuggable models

On the other hand, Streamlit provides the following key features:

• Free and open source
• Build apps in a dozen lines of Python with a simple API
• No callbacks

Aerosolve and Streamlit are both open source tools. Aerosolve with 4.58K GitHub stars and 581 forks on GitHub appears to be more popular than Streamlit with 2.73K GitHub stars and 184 GitHub forks.