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name
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title
Home
description
Semantic, grammar, language, etc
image
site name
Semagle
author
updated
2025-12-30 07:55:28
raw text
HOME | SEMAGLE Semagle Semagle Home Blog Feed Semagle F# Framework Applied machine learning developers have a lot of open-source machine learning frameworks, e.g., ScikitLearn , Spark MLlib , ML.Net , etc. Frameworks provide a user-friendly high-level interface to algorithms, but implementations resort to low-level languages and optimizations. Such low-level C/C++, C#, or Java code is far from the original mathematical notation that is preferable for machine learning algorithms research and development. Semagle Framework makes the most of low-level C#-like constructs for performance optimization and high-level semi-mathematical F# notation for joining the algorithm blocks. Modularization of algorithms with fine-grained blocks makes research and development of new implementations for the same family of problems straightforward. Semagle Building Trees from Materialized Paths Materialized path or path enumeration model1 stores the path to the tree node as a strin...
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