Step-by-step concept proof and examle of the Least Square Method for Linear Regression using R language. The code is long with the purpose to show what goes under the hood in a linear regression calculation.
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Updated
Dec 27, 2019 - R
Step-by-step concept proof and examle of the Least Square Method for Linear Regression using R language. The code is long with the purpose to show what goes under the hood in a linear regression calculation.
Concept Generator utilizes ChatGPT 3.5 to generate multifaceted data about concepts, which are fundamental building blocks in thinking. The project yields three types of data: Relational, Comparative, and Descriptive. It's designed for learners, educators, researchers, and anyone curious about the intricacies of human thought.
A concept extractor for Twitter.
Severity-focused biomedical concept normalization in Python
The replication package of STRICT: Search Term Identification for Concept Location using Graph-Based Term Weighting
Concept Extraction from medical discharge summaries
Concept Explorer is an educational web app designed to make exploring concepts as exciting as exploring the physical world. It uses AI-powered data generated by the Concept Generator project to provide engaging and interactive concept exploration.
The proposed system provides high-quality augmentations for educational texts like concept definitions, applications, equations, and examples for improved user understanding.
Concept extraction from MIMIC3 notes
REST-API for LearningMiner.
Web Of Things Ontology Inspection
A toolkit to do concept expansion via search engine snippet
Clinical text-mining/machine learning project I did as part of my masters thesis at LIG.
Combining Energy-Based Modeling and RL to solve the challenging Abstract Reasoning Corpus[1] tasks.
Retrospective Extraction of Visual and Logical Insights for Ontology-based interpretation of Neural Networks
Python code for construction and analysis of semantic networks from text.
Software created within Accumulate project (www.accumulate.be) at CLiPS, University of Antwerp
create concept map from textbook data
CME: Concept-based Model Extraction
Simple spaCy-based concept extraction API, involving a dictionary of relevant concepts.
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