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Binomial regression
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Related lectures (27)
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Generalized Linear Models: Theory and Applications
Covers the theory and applications of Generalized Linear Models, including MLE, measures of fit, shrinkage, and special examples.
Textual Data Analysis: Classification & Dimensionality Reduction
Explores textual data classification, focusing on methods like Naive Bayes and dimensionality reduction techniques like Principal Component Analysis.
Horseshoe Crabs: Logistic Regression Analysis
Explores logistic regression analysis of horseshoe crab data, focusing on odds ratio interpretation and model fitting.
Estimation and Analysis of Deviance
Covers estimation of unknown parameters, analyzing model fit, bird prey response, and model diagnostics.
Deep Learning: Edge Detection and Neural Networks
Discusses edge detection techniques and the evolution of deep learning in neural networks.
Linear and Logistic Regression
Covers linear and logistic regression, including underfitting, overfitting, and performance metrics.
Untitled
Generalized Linear Regression: Classification
Explores Generalized Linear Regression, Classification, confusion matrices, ROC curves, and noise in data.
Generalised Linear Models: Regression with Exponential Family Responses
Covers regression with exponential family responses using Generalised Linear Models.
Linear Regression Essentials
Covers the essentials of linear regression, focusing on using multiple quantitative explanatory variables to predict a quantitative outcome.