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Showing 241 - 243 results of 243 for search '(( python model implementation ) OR ( python time implementation ))', query time: 0.19s Refine Results
  1. 241
    Data Sheet 1_COCαDA - a fast and scalable algorithm for interatomic contact detection in proteins using Cα distance matrices.pdf

    Data Sheet 1_COCαDA - a fast and scalable algorithm for interatomic contact detection in proteins using Cα distance matrices.pdf by Rafael Pereira Lemos (9104911)

    Published 2025
    “…COCαDA demonstrated superior performance compared to the other methods, achieving on average 6x faster computation times than advanced data structures like k-d trees from NS, in addition to being simpler to implement and fully customizable. …”
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  2. 242
    IGD-cyberbullying-detection-AI

    IGD-cyberbullying-detection-AI by Bryan James (19921044)

    Published 2024
    “…[<a href="https://doi.org/10.6084/m9.figshare.27266961" rel="nofollow" target="_blank">https://doi.org/10.6084/m9.figshare.27266961</a>]</p><h2>Table of Contents</h2><ul><li><a href="https://github.com/BryanSJamesDev/IGD-cyberbullying-detection-AI#overview" target="_blank">Overview</a></li><li><a href="https://github.com/BryanSJamesDev/IGD-cyberbullying-detection-AI#requirements" target="_blank">Requirements</a></li><li><a href="https://github.com/BryanSJamesDev/IGD-cyberbullying-detection-AI#datasets" target="_blank">Datasets</a></li><li><a href="https://github.com/BryanSJamesDev/IGD-cyberbullying-detection-AI#installation" target="_blank">Installation</a></li><li><a href="https://github.com/BryanSJamesDev/IGD-cyberbullying-detection-AI#running-the-code" target="_blank">Running the Code</a></li><li><a href="https://github.com/BryanSJamesDev/IGD-cyberbullying-detection-AI#expected-results" target="_blank">Expected Results</a></li></ul><h2>Overview</h2><p dir="ltr">This repository provides the code for predicting mental health outcomes associated with Internet Gaming Disorder (IGD) and Cyberbullying using machine learning and deep learning models. Models like Logistic Regression, Random Forest, Ensemble Models, CNNs, and LSTMs are implemented to detect patterns from behavioral data.…”
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  3. 243
    Comprehensive Fluid and Gravitational Dynamics Script for General Symbolic Navier-Stokes Calculations and Validation

    Comprehensive Fluid and Gravitational Dynamics Script for General Symbolic Navier-Stokes Calculations and Validation by Stylianos Touloumidis (19938747)

    Published 2024
    “…It provides a flexible foundation on which theoretical assumptions can be validated, and practical calculations performed. Implemented in Python with symbolic calculations, the script facilitates in-depth analysis of complex flow patterns and makes advanced mathematical computations more accessible. …”
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