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Introduction to computational causal inference using reproducible Stata, R, and Python code: A tutorial by Smith, Matthew J., Mansournia, Mohammad A., Maringe, Camille, Zivich, Paul N., Cole, Stephen R., Leyrat, Clémence, Belot, Aurélien, Rachet, Bernard, Luque‐Fernandez, Miguel A.

“…The main purpose of many medical studies is to estimate the effects of a treatment or exposure on an outcome. However, it is not always possible to randomize…”
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Percolation theory using Python by Malthe-Sørenssen, Anders

“… 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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Statistics Using Python by Campesato, Oswald

“…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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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

“… This application enables the comparison of triggered alarms with the resultant logical states obtained during the analysis…”
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Manifold Markov chain Monte Carlo methods for Bayesian inference in diffusion models by Graham, Matthew M., Thiery, Alexandre H., Beskos, Alexandros

“…Bayesian inference for nonlinear diffusions, observed at discrete times, is a challenging task that has prompted the development of a number of algorithms,…”
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Using GNU Make to Manage the Workflow of Data Analysis Projects by Baker, Peter

“…Data analysis projects invariably involve a series of steps such as reading, cleaning, summarizing and plotting data, statistical analysis and reporting…”
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Trimmed Constrained Mixed Effects Models: Formulations and Algorithms by Zheng, Peng, Barber, Ryan, Sorensen, Reed J. D., Murray, Christopher J. L., Aravkin, Aleksandr Y.

“…Mixed effects (ME) models inform a vast array of problems in the physical and social sciences, and are pervasive in meta-analysis…”
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Prediction of Positive Patient Health Questionnaire-2 Screening Using Area Deprivation Index in Primary Care by Duarte, Martha, Salamanca, Mayra, Gonzalez, Juan M, Roman Laporte, Roberto, Gattamorta, Karina, Lopez Martinez, Fernando Enrique, Clochesy, John, Rincon Acuna, Juan Carlos

“…Depression is recognized as a significant public health issue in the United States. The National Survey on Drug Use and Health reports that 21.0 million adults…”
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A Review of Adversarial Attack and Defense for Classification Methods by Li, Yao, Cheng, Minhao, Hsieh, Cho-Jui, Lee, Thomas C. M.

“…Despite the efficiency and scalability of machine learning systems, recent studies have demonstrated that many classification methods, especially Deep Neural…”
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Unit information prior for adaptive information borrowing from multiple historical datasets by Jin, Huaqing, Yin, Guosheng

“… Incorporating historical data in the analysis of the current study is of great importance, as it can help to gain more information, improve efficiency, and provide a more comprehensive evaluation of treatment…”
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Domain-specific decision modelling and statistical analysis for combat system effectiveness simulation by Li, Xiaobo, Lei, Yonglin, Vangheluwe, Hans, Wang, Weiping, Li, Qun

“… decision models to Python code which is supported by a Python script framework to implement decision models and we present a Bayesian network-based statistical analysis method on simulation output data…”
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Graph analysis and visualization: discovering business opportunity in linked data by Brath, Richard, Jonker, David

“… The companion website offers data sets, full code examples in Python, and links to all the tools covered in the book…”
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Fitting deep neural networks into the statistical regression modelling setting by Ha, Il Do, Burke, Kevin

“… The Appendix provides Python codes for a TensorFlow-Keras implementation so that a GLM-based DNN becomes directly accessible to interested readers, including the codes of Cox-based DNN…”
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Spatial Analysis Using Big Data by Hajime Seya, Yoshiki Yamagata

“…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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Weather Prediction Using Logistic Regression (AI/ML Techniques)

“…’ steps along with choosing responsible dependent or independent parameters called as predictors to find results or outputs by various machine learning packages of Python like ‘Pandas’, ‘SEABORN’, ‘STATS MODEL’ etc. ,under ‘SCIKIT LEARN…”
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Modelo de series de tiempo para predecir la demanda de atención de pacientes con enfermedad renal crónica, 2022 by Espinoza Melgarejo, José Luis

“…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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