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Tom's Obvious, Minimal Language (TOML, originally Tom's Own Markup Language [2]) is a file format for configuration files. [3] It is intended to be easy to read and write due to obvious semantics which aim to be "minimal", and it is designed to map unambiguously to a dictionary. Originally created by Tom Preston-Werner, its specification is ...
Martin Toml (born 25 March 1996) is a Czech professional footballer who currently plays as a centre back for Chrudim. [2] References External links. FC ...
Across Unix-like operating systems many different configuration-file formats exist, with each application or service potentially having a unique format, but there is a strong tradition of them being in human-editable plain text, and a simple key–value pair format is common.
Preston-Werner grew up in Dubuque, Iowa.His father died when he was a child. His mother was a teacher and his stepfather was an engineer. [11]He graduated from high school at Dubuque Senior High School and attended Harvey Mudd College in Claremont, California for 2 years before dropping out to pursue other endeavours.
YAML (/ ˈ j æ m əl /, rhymes with camel [4]) was first proposed by Clark Evans in 2001, [15] who designed it together with Ingy döt Net [16] and Oren Ben-Kiki. [16]Originally YAML was said to mean Yet Another Markup Language, [17] because it was released in an era that saw a proliferation of markup languages for presentation and connectivity (HTML, XML, SGML, etc.).
The following outline is provided as an overview of, and topical guide to, machine learning: . Machine learning (ML) is a subfield of artificial intelligence within computer science that evolved from the study of pattern recognition and computational learning theory. [1]
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]
TOMLAB supports solvers like CPLEX, SNOPT, KNITRO and MIDACO.Each such solver can be called to solve one single model formulation. The supported solvers are appropriate for many problems, including linear programming, integer programming, and global optimization.