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SPGeneralized Linear Model in PythonGeneralised Linear Model (GLM) is one of many models to form the linear relationship between the dependent variable and its predictors…Oct 10, 2022Oct 10, 2022
Jacob MazurkiewiczHow Logistic Regression Actually WorksLogistic regression is one of the most powerful linear models for classification. Here’s how it really works.Oct 14Oct 14
Nilimesh Halder, PhDUnderstanding Residual Plots in Linear Regression Models: A Comprehensive Guide with ExamplesLinear regression is a widely used statistical method for analyzing the relationship between a dependent variable and one or more…Mar 24, 2023Mar 24, 2023
InTowards Data SciencebySachin DateOmitted Variable BiasAn intro to an especially sneaky bias that invades many regression modelsAug 62
SPGeneralized Linear Model in PythonGeneralised Linear Model (GLM) is one of many models to form the linear relationship between the dependent variable and its predictors…Oct 10, 2022
Jacob MazurkiewiczHow Logistic Regression Actually WorksLogistic regression is one of the most powerful linear models for classification. Here’s how it really works.Oct 14
Nilimesh Halder, PhDUnderstanding Residual Plots in Linear Regression Models: A Comprehensive Guide with ExamplesLinear regression is a widely used statistical method for analyzing the relationship between a dependent variable and one or more…Mar 24, 2023
Souvik TaAn Introduction to Linear Model Identification: Ordinary Least Squares (OLS) with PythonIn the realm of dynamic systems modeling — particularly in engineering, control theory, and systems biology — the State Space Model…Oct 11
NitinKumar SharmaSimple Linear Regression Roadmap: From Data to Best-Fit LineCertainly! I’ll explain simple linear regression in a way that a 15-year-old can understand, covering the topics of the regression line…Oct 23, 2023
Fahad HussainUnderstanding Noisy Data with Linear RegressionIn data science, real-world datasets are often messy and noisy. A common approach to uncover trends in such data is linear regression. This…Oct 4