[[["容易理解","easyToUnderstand","thumb-up"],["確實解決了我的問題","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["缺少我需要的資訊","missingTheInformationINeed","thumb-down"],["過於複雜/步驟過多","tooComplicatedTooManySteps","thumb-down"],["過時","outOfDate","thumb-down"],["翻譯問題","translationIssue","thumb-down"],["示例/程式碼問題","samplesCodeIssue","thumb-down"],["其他","otherDown","thumb-down"]],["上次更新時間：2024-11-08 (世界標準時間)。"],[[["This module introduces logistic regression, a model used to predict the probability of an outcome, unlike linear regression which predicts continuous numerical values."],["Logistic regression utilizes the sigmoid function to calculate probability and employs log loss as its loss function."],["Regularization is crucial when training logistic regression models to prevent overfitting and improve generalization."],["The module covers the comparison between linear and logistic regression and explores use cases for logistic regression."],["Familiarity with introductory machine learning and linear regression concepts is assumed for this 35-minute module."]]],[]]
