Regularized Logistic Regression Regularization is a process of introducing additional information in order to solve an ill-posed problem or to prevent overfitting machine-learning andrew-ng

Basics of Language Model Language modeling is used in speech recognition, machine translation, part-of-speech tagging, parsing, handwriting recognition, information retrieval and other applications. NLP machine-learning

Regularized Linear Regression Regularization is a process of introducing additional information in order to solve an ill-posed problem or to prevent overfitting machine-learning andrew-ng

Overfitting and Regularization Overfitting occurs when a model is excessively complex, such as having too many parameters relative to the number of observations machine-learning andrew-ng

Multiclass Logistic Regression Application of logistic regression to multi-dimensional datasets. It is a generalization of the binary logistic regression. machine-learning andrew-ng

Logistic Regression Model Mathematics and Implementation of training a logistic regression model machine-learning andrew-ng

Classification and Logistic Regression Logistic regression, or logit regression, or logit model is a regression model where the dependent variable is categorical machine-learning andrew-ng

Normal Equation Given a matrix equation, the normal equation is one which minimizes the sum of the square differences between the left and right sides machine-learning mathematics andrew-ng

Multivariate Linear Regression When linear regression is applied on a higher-dimensional dataset, a generalization of linear regression is obtained machine-learning andrew-ng