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The Pythonic Way: An Architect's Guide to Conventions and Best Practices for the Design, Development, Testing, and Management of Enterprise Python Code

by Raj, Sonal
Year of Publication 2021

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eBook

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Anyone Can Code: The Art and Science of Logical Creativity

by Arya, Ali
Year of Publication 2021

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eBook Book

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Causal Inference and Discovery in Python: Unlock the secrets of modern causal machine learning with DoWhy, EconML, PyTorch and more

by Molak, Aleksander
Year of Publication 2023

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Computer Architecture with Python and ARM: Learn How Computers Work, Program Your Own, and Explore Assembly Language on Raspberry Pi

by Clements, Alan
Year of Publication 2023

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Comparison of Artificial Intelligence Techniques to Evaluate Performance of a Classifier for Automatic Grading of Prostate Cancer From Digitized Histopathologic Images

by Nir, Guy, Karimi, Davood, Goldenberg, S. Larry, Fazli, Ladan, Skinnider, Brian F., Tavassoli, Peyman, Turbin, Dmitry, Villamil, Carlos F., Wang, Gang, Thompson, Darby J. S., Black, Peter C., Salcudean, Septimiu E.
Published in JAMA network open (01.03.2019)

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Journal Article

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Thermal error compensation of a 5-axis machine tool using indigenous temperature sensors and CNC integrated Python code validated with a machined test piece

by Mareš, Martin, Horejš, Otakar, Havlík, Lukáš
Published in Precision engineering (01.11.2020)

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Journal Article

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21CMMC: an MCMC analysis tool enabling astrophysical parameter studies of the cosmic 21 cm signal

by Greig, Bradley, Mesinger, Andrei
Published in Monthly notices of the Royal Astronomical Society (01.06.2015)

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Journal Article

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Switching function based on hypergraphs with algorithm and python programming

by Hamidi, Mohammad, Rahmati, Marzieh, Rezaei, Akbar
Published in Journal of intelligent & fuzzy systems (01.01.2020)

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Journal Article

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ParamGULP: An efficient Python code for obtaining interatomic potential parameters for General Utility Lattice Program

by Dutra, José Diogo L., Bispo, Thiago D., de Freitas, Sabrina M., Rezende, Marcos V. dos S.
Published in Computer physics communications (01.08.2021)

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Journal Article

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Genetic algorithms and machine learning for programmers : create AI models and evolve solutions

by Buontempo, Frances
Year of Publication 2019

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A framework to create customised LHC analyses within CheckMATE

by Kim, Jong Soo, Schmeier, Daniel, Tattersall, Jamie, Rolbiecki, Krzysztof
Published in Computer physics communications (01.11.2015)

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Journal Article

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Extended computational kernels in a massively parallel implementation of the Trotter–Suzuki approximation

by Wittek, Peter, Calderaro, Luca
Published in Computer physics communications (01.12.2015)

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Journal Article

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Genome sequencing technology and algorithms

by Kim, Sun, Mardis, Elaine, Tang, Haixu
Year of Publication 2007

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eBook Book

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FDTool: a Python application to mine for functional dependencies and candidate keys in tabular data [version 2; peer review: 2 approved]

by Buranosky, Matt, Stellnberger, Elmar, Pfaff, Emily, Diaz-Sanchez, David, Ward-Caviness, Cavin
Published in F1000 research (2018)

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Journal Article

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Fuzzy Logic, Neural Network, and Adaptive Neuro-Fuzzy Inference System in Delegation of Standard Concrete Beam Calculations

by Baghdadi, Abtin, Babovic, Neira, Kloft, Harald
Published in Buildings (Basel) (01.01.2024)

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Journal Article

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General Purpose Convolution Algorithm in S 4 Classes by Means of FFT

by Ruckdeschel, Peter, Kohl, Matthias
Published in Journal of statistical software (2014)

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Journal Article

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Time Series Indexing: Implement iSAX in Python to index time series with confidence

by Tsoukalos, Mihalis
Year of Publication 2023

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Quantitative X-ray Map Analyser (Q-XRMA): A new GIS-based statistical approach to Mineral Image Analysis

by Ortolano, Gaetano, Visalli, Roberto, Godard, Gaston, Cirrincione, Rosolino
Published in Computers & geosciences (01.06.2018)

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Journal Article

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NanoNET: an extendable Python framework for semi-empirical tight-binding models

by Klymenko, M V, Vaitkus, J A, Smith, J S, Cole, J H
Published in arXiv.org (15.10.2020)

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Paper Journal Article

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The Deep Learning with Keras Workshop: Learn How to Define and Train Neural Network Models with Just a Few Lines of Code

by Moocarme, Matthew, Abdolahnejad, Mahla, Bhagwat, Ritesh
Year of Publication 2020

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