Mental Models 4 Life

Escher

Escher is a functional logic programming language designed with the aim of providing in a simple computation mechanism the best features of functional programming and logic programming. Escher is described in more details in these articles:

• Declarative Programming in Escher
• Programming in an Integrated Functional and Logic Language

The theoretical foundations for Escher is provided in the book `Logic for Learning’ by John Lloyd.

Escher is implemented in Noweb-C++, with fairly extensive documentation. It is being actively supported.

• Here’s the literate program An Implementation of Escher.
• The source files are hosted on Github: https://github.com/keesiong/escher

Apache MADlib

MADlib is a scalable in-database machine learning algorithm. It is recently accepted as an incubator project by ASF after 5 years of development and it is available here: http://madlib.net

MADlib’s design philosophy and implementation details can be found in these two VLDB papers:

• The MADlib Analytics Library or MAD Skills, the SQL
• MAD Skills: New Analysis Practices for Big Data