psaris/funq
Source files for "Fun Q: A Functional Introduction to Machine Learning in Q"
This project offers practical examples for applying machine learning techniques within the Q programming language, commonly used in financial markets. It provides the underlying code for various algorithms, allowing users to input their datasets and build models for tasks like classification, regression, and clustering. This is intended for quantitative analysts, traders, or financial engineers who work with Q and kdb+ and want to implement machine learning solutions.
140 stars. No commits in the last 6 months.
Use this if you are a quantitative professional familiar with Q and kdb+ and want to learn or implement machine learning algorithms directly within that environment.
Not ideal if you are looking for a general-purpose machine learning library in Python or R, or if you are unfamiliar with the Q programming language.
Stars
140
Forks
56
Language
q
License
MIT
Category
Last pushed
Oct 13, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/psaris/funq"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
lucasmaystre/choix
Inference algorithms for models based on Luce's choice axiom
laresbernardo/lares
Analytics & Machine Learning R Sidekick
TheAlgorithms/R
Collection of various algorithms implemented in R.
easystats/performance
:muscle: Models' quality and performance metrics (R2, ICC, LOO, AIC, BF, ...)
mlr-org/mlr
Machine Learning in R