There are two major categories of problems that are often solved by machine learning: regression and classification. Regression is for numeric data (e.g. What is the likely income for someone with ...

AUC-ROC is the valued metric used for evaluating the performance in classification models ... The metrics that one chooses to evaluate a machine learning model play an important role. The choice of ...

This requires basic machine learning literacy — what kinds of problems can machine learning solve, and how to talk about those problems with data scientists. Linear regression and feature ...

logistic regression WEEK 12 - Neural networks; Multi-layer perceptron, activation functions; Training - SGD and back propagation; Hyperparameters - number of layers, neurons, activation functions.

Google has updated its machine learning crash course with ... to the fundamentals of Linear Regression, Logistic Regression, and Binary Classification Models The Large Language Models module ...

Building from the simplest to the most sophisticated methods of machine learning, the books give several hands-on examples of coding to assist readers in understanding both the methods and their ...

Abstract: This work presents an approach how machine learning techniques can be utilized ... monitoring globally by using a combination of classification and regression methods, and at the same time ...