[{"data":1,"prerenderedAt":37},["ShallowReactive",2],{"post-document:\u002Fdeep_learning\u002Fbasic\u002F2026\u002F08\u002F06\u002Fdeep-learning-basics\u002F":3},{"id":4,"title":5,"body":6,"categories":17,"date":20,"description":21,"extension":22,"image":23,"key_concepts":23,"last_modified_at":23,"legacyPath":24,"meta":25,"navigation":27,"part":23,"path":28,"published":27,"robots":23,"seo":29,"series":23,"stem":30,"strengths":23,"summary":31,"tags":32,"tradeoffs":23,"__hash__":36},"posts\u002Fposts\u002FDeep_Learning\u002FBasic\u002F2026-08-06-deep-learning-basics.md","딥러닝 학습 기본 개념",{"type":7,"value":8,"toc":13},"minimark",[9],[10,11,12],"p",{},"딥러닝 학습은 실제로 어떤 순서로 진행되는가\nEpoch, Batch, Iteration의 차이\nTrain, Validation, Test 데이터 분리\nForward, Loss, Backward, Optimizer 흐름\nParameter와 Hyperparameter의 차이\nClassification, Detection, Segmentation 차이\nFeature, Label, Logit, Probability의 의미\nPretrained Model을 사용하는 이유\nFine-tuning과 Transfer Learning 차이\nInference와 Training의 차이",{"title":14,"searchDepth":15,"depth":15,"links":16},"",2,[],[18,19],"Deep_Learning","Basic","2026-08-06 00:00:00 +0900","딥러닝 학습 흐름과 Epoch, Batch, 데이터 분리, 학습 및 추론의 기본 개념을 정리한다.","md",null,"\u002Fdeep_learning\u002Fbasic\u002F2026\u002F08\u002F06\u002Fdeep-learning-basics\u002F",{"layout":26},"post",true,"\u002Fposts\u002Fdeep_learning\u002Fbasic\u002F2026-08-06-deep-learning-basics",{"title":5,"description":21},"posts\u002FDeep_Learning\u002FBasic\u002F2026-08-06-deep-learning-basics","딥러닝을 시작할 때 알아야 할 학습 과정과 핵심 용어를 정리한다.",[33,34,35],"Deep Learning","Machine Learning","Training Basics","RuppbtS2ChJkwzyj-RBLmORI0hK2pUJSqNdCGnmOUMk",1788744788491]