Aerosolve vs Amazon Personalize

Aerosolve vs Amazon Personalize: 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 Amazon Personalize? Real-time personalization and recommendation. Machine learning service that makes it easy for developers to add individualized recommendations to customers using their applications.

Aerosolve can be classified as a tool in the "Machine Learning Tools" category, while Amazon Personalize is grouped under "Machine Learning as a Service".

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, Amazon Personalize provides the following key features:

• Combine customer and contextual data to generate high-quality recommendations
• Automated machine learning
• Continuous learning to improve performance

Aerosolve is an open source tool with 4.58K GitHub stars and 578 GitHub forks. Here's a link to Aerosolve's open source repository on GitHub.