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  1. 1

    Percolation theory using Python by Malthe-Sørenssen, Anders

    ISBN: 3031598997, 9783031598999, 3031599004, 9783031599002
    Published: Cham Springer 2024
    “… Readers will learn how to generate, analyze, and comprehend data and models, with detailed theoretical discussions complemented by accessible computer codes…”
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    eBook Book
  2. 2

    Statistics Using Python by Campesato, Oswald

    ISBN: 9781683928805, 1683928806
    Published: Berlin Mercury Learning and Information 2024
    “…This book is designed to offer a fast-paced yet thorough introduction to essential statistical concepts using Python code samples, and aims to assist data scientists in their daily endeavors…”
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  3. 3

    From code to reliability: Python-powered Paraconsistent Logic for alarm detection in the power gris/ Do codigo a confiabilidade: Logica Paraconsistente impulsionada por Python para a deteccao de alarmes na rede de energia by de Oliveira, Joseffe Barroso, Gino, Joao Vitor Santa Rosa, de Lima, Carlos Jose, Filho, Joao Inacio da Silva

    ISSN: 2178-9010, 2178-9010
    Published: Sindicato das Secretarias e Secretarios do Estado de Sao Paulo 01.10.2023
    Published in GeSec : Revista de Gestão e Secretariado (01.10.2023)
    “… This application enables the comparison of triggered alarms with the resultant logical states obtained during the analysis…”
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    Journal Article
  4. 4

    Leveraging machine learning for accurate DNBR prediction using python by Mohamed Y.M. Mohsen, Meshari Al Meshari, Yasser Alzamil, Abdulrahman Alhammad, Khaled Alenazi, Atef El-Taher, Tarek F. Nagla, Mohamed A.E. Abdel-Rahman

    ISSN: 1738-5733, 2234-358X
    Published: 2025
    “…This study investigates the viability of using Python scikit-learn packages, specifically regression techniques, to forecast the departure from nucleate boiling ratio (DNBR…”
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    Journal Article
  5. 5

    Using DeepLabCut for 3D markerless pose estimation across species and behaviors by Nath, Tanmay, Mathis, Alexander, Chen, An Chi, Patel, Amir, Bethge, Matthias, Mathis, Mackenzie Weygandt

    ISSN: 1754-2189, 1750-2799, 1750-2799
    Published: England Nature Publishing Group 01.07.2019
    Published in Nature protocols (01.07.2019)
    “… We recently introduced an open-source toolbox called DeepLabCut that builds on a state-of-the-art human pose-estimation algorithm to allow a user to train a deep neural network with limited training…”
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    Journal Article
  6. 6

    Is Multitask Deep Learning Practical for Pharma? by Ramsundar, Bharath, Liu, Bowen, Wu, Zhenqin, Verras, Andreas, Tudor, Matthew, Sheridan, Robert P, Pande, Vijay

    ISSN: 1549-960X, 1549-960X
    Published: United States 28.08.2017
    “… Our implementation enables simple python scripts to construct, fit, and evaluate sophisticated deep models…”
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    Journal Article
  7. 7

    ROOT — A C++ framework for petabyte data storage, statistical analysis and visualization by Antcheva, I., Ballintijn, M., Bellenot, B., Biskup, M., Brun, R., Buncic, N., Canal, Ph, Casadei, D., Couet, O., Fine, V., Franco, L., Ganis, G., Gheata, A., Maline, D. Gonzalez, Goto, M., Iwaszkiewicz, J., Kreshuk, A., Segura, D. Marcos, Maunder, R., Moneta, L., Naumann, A., Offermann, E., Onuchin, V., Panacek, S., Rademakers, F., Russo, P., Tadel, M.

    ISSN: 0010-4655, 1879-2944, 1386-9485
    Published: Elsevier B.V 2011
    Published in Computer physics communications (2011)
    “…A new stable version (“production version”) v5.28.00 of ROOT [1] has been published [2]. It features several major improvements in many areas, most noteworthy…”
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    Journal Article
  8. 8
  9. 9

    Spatial Analysis Using Big Data by Hajime Seya, Yoshiki Yamagata

    ISBN: 0128131322, 9780128131329
    Published: Academic Press 03.11.2019
    “…Spatial Analysis Using Big Data: Methods and Urban Applications helps readers understand the most powerful, state-of-the-art spatial econometric methods, focusing particularly on urban research problems…”
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  10. 10

    Machine learning : a Bayesian and optimization perspective by Theodoridis, Sergios

    ISBN: 9780128188033, 0128188030
    Published: London Academic Press 2020
    “…Machine Learning: A Bayesian and Optimization Perspective, Second Edition, gives a unifying perspective on machine learning by covering both probabilistic and…”
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  11. 11

    Modelo de series de tiempo para predecir la demanda de atención de pacientes con enfermedad renal crónica, 2022 by Espinoza Melgarejo, José Luis

    ISSN: 1996-7551, 2707-9368
    Published: 27.12.2024
    Published in Revista I+i (27.12.2024)
    “…The main objective of this study is to forecast the demand for patients with chronic kidney disease in state-run healthcare facilities in Peru in 2022 using time series models, and to conduct…”
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    Journal Article