[[["เข้าใจง่าย","easyToUnderstand","thumb-up"],["แก้ปัญหาของฉันได้","solvedMyProblem","thumb-up"],["อื่นๆ","otherUp","thumb-up"]],[["ไม่มีข้อมูลที่ฉันต้องการ","missingTheInformationINeed","thumb-down"],["ซับซ้อนเกินไป/มีหลายขั้นตอนมากเกินไป","tooComplicatedTooManySteps","thumb-down"],["ล้าสมัย","outOfDate","thumb-down"],["ปัญหาเกี่ยวกับการแปล","translationIssue","thumb-down"],["ตัวอย่าง/ปัญหาเกี่ยวกับโค้ด","samplesCodeIssue","thumb-down"],["อื่นๆ","otherDown","thumb-down"]],["อัปเดตล่าสุด 2024-11-08 UTC"],[[["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."]]],[]]
