When it comes to open source recommendation engines tailored for insurance recommendations, two popular choices are:

• ActionML Engines: This open source project provides a collection of recommendation engines, including the Universal Recommender, which can be customized for insurance recommendations based on user behavior and other relevant data.
• Cornac: Cornac is a flexible and scalable recommender system library in Python. It offers various recommendation algorithms that can be adapted to suit insurance recommendations by incorporating domain-specific features and data.

Both ActionML Engines and Cornac provide a solid foundation for building and customizing recommendation engines for insurance applications. You can explore their documentation, code repositories, and community support to determine which one aligns best with your requirements.

Tags: Insurance, Recommendation Engine

Recently, the language model community has been buzzing with discussions about the performance of various models. A particular model that caught our attention is Beyonder , which, in casual testing, seems to be one of the rare non-broken Mixture of Experts (MoEs). It incorporates openchat-3.5 , a model previously benchmarked by the community.

But what's the best inference engine? This question often arises, and it's crucial to consider the source code … click here to read