Prolog for Data Science

This page summarizes the projects mentioned and recommended in the original post on news.ycombinator.com

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  • Popper

    An inductive logic programming system (by logic-and-learning-lab)

  • I finished my master's thesis in Inductive Logic Programming recently at Oxford. I'd say that the field has continued improving since Aleph, which was written in the late 90s.

    Anyone interested could also take a look at Popper (https://github.com/logic-and-learning-lab/Popper) or this overview of the first 30 years of ILP (https://arxiv.org/abs/2008.07912)

  • csuite-saas-metric-generator

    Tell ‘em what they want to hear!

  • I made the c-suite SaaS metrics generator especially for those types of managers!

    https://github.com/patricktrainer/csuite-saas-metric-generat...

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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  • I made the c-suite SaaS metrics generator especially for those types of managers!

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  • mangle

  • Logic programming offers a good foundation for anything that people call "rule engines." Within logic programming, there is some variation on the degree of declarativeness.

    Datalog is arguably the minimal core logic programming, similar to what the lambda calculus achieves for functional programming. Unfortunately, it has been forgotten outside of database and query processing realm. A resurgence has happened in recent years, as PL researchers and also industry have discovered the virtues of datalog (e.g. Flix, DataFun). My own attempt at making this more widely known is here https://github.com/google/mangle, a language from the datalog family and its implementation as a go library.

    As the example shows: plain "rules" (or: plain datalog) is rarely enough to capture everything that one wants to express: the question then is, how to combine a pure declarative "kernel" with more general purpose programming (e.g. mapping a list).

    PROLOG offered one answer, already in the 1980s, but I fully reject it: the fact that the writing a program in the wrong order with negation and recursion makes it non-terminating is not something we'd want everyone to deal with. Datalog with stratified recursion is somewhat better, as "layers of rules" is a concept that is easy to understand.

    In mainstream programming languages, the possibility of writing non-terminating programs also exists, but is rarely an issue. That is why I believe a good combination of declarative and general-purpose has to make it really easy to recognize which parts of a program are in the declarative, terminating, safe kernel and which parts require more attention from the programmer.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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