머신러닝 입문강의 24년 버전 - [국내 Top AI대학원 박사] - 15만 조회수 기록강의

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⚡강의 목차
00:00:00 인트로
00:03:00 What is Machine Learning
00:19:00 강의 목차
00:24:22 ML vs DL
00:27:18 Regression vs Classification
00:31:06 Notations
00:53:35 Basic Math for ML
01:27:23 Linear Regression
01:33:41 How to find optimal parameters
01:36:12 Advanced math for ML
01:42:48 Loss function
01:45:16 최소 제곱법
01:58:48 Gradient Descent
02:14:18 Advanced Gradient Descent
02:28:49 Training data vs Test data
02:34:02 Bias and Variance Trade-off
03:02:30 How to solve that trade-off
03:03:07 Validation data
03:06:26 Leave-One-Out Cross-Validation
03:09:31 K-fold cross validation
03:15:00 Regularization
03:17:28 Ridge Regression
03:26:07 Regularization