[[["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 2024-08-22 UTC"],[[["Neural networks with the same architecture and data can converge to different solutions due to random initialization, highlighting its role in non-convex optimization."],["Increasing the complexity of a neural network by adding layers and nodes can improve the stability and repeatability of training results, leading to more consistent model performance."],["Initialization significantly impacts the final model and the variance in test loss, especially in simpler network structures."],["While simpler networks can exhibit diverse solutions and varying losses, more complex models demonstrate increased stability and repeatable convergence."]]],[]]
