1. |
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강의소개/인공지능 소개 |
강의 소개 및 인공지능 소개 |
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2. |
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선형대수 리뷰 |
머신러닝을 위한 선형대수 리뷰 |
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3. |
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확률통계 리뷰 |
머신러닝을 위한 확률통계 리뷰 |
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4. |
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Decision Theory |
classification 관련 decision theory |
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Decision Theory_part 1 |
classification 관련 decision theory |
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Decision Theory_part 2 |
classification 관련 decision theory |
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Decision Theory_part 3 |
classification 관련 decision theory |
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Decision Theory_disc_func. |
classification 관련 decision theory |
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5. |
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Information Theory |
Information Theory |
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Information Theory |
Information Theory |
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6. |
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분류 |
분류알고리즘(kNN, Naïve Bayes Classifier, decision tree, rnadom forest, ensemble learning 등) |
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분류_kde_knn |
분류알고리즘(kNN, Naïve Bayes Classifier, decision tree, rnadom forest, ensemble learning 등) |
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분류_NB_DT_part1 |
분류알고리즘(kNN, Naïve Bayes Classifier, decision tree, rnadom forest, ensemble learning 등) |
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분류_NB_DT_part2 |
분류알고리즘(kNN, Naïve Bayes Classifier, decision tree, rnadom forest, ensemble learning 등) |
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7. |
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Clustering |
kMeans, mixture of Gaussian, expectation maximization |
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Clustering_kMeans |
kMeans, mixture of Gaussian, expectation maximization |
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Clustering_MoG_EM_part1 |
kMeans, mixture of Gaussian, expectation maximization |
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Clustering_MoG_EM_part2 |
kMeans, mixture of Gaussian, expectation maximization |
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8. |
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Kernel Machines_PCA_MDS_part1 |
kernel machines (PCA, MDS, LDA) |
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Kernel Machines_PCA_MDS_part2 |
kernel machines (PCA, MDS, LDA) |
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Kernel Machines_KPCA_Manifold |
kernel machines (PCA, MDS, LDA) |
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Kernel Machines_LDA_ICA |
kernel machines (kernel PCA, kernel LDA ICA) |
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9. |
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Kernel Machines |
kernel machines (kernel PCA, kernel LDA ICA) |
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10. |
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추천시스템 |
recommendation systems (content based and collaborative filtering) and matrix factorizations (non-negative matrix factorization, Cholesky decomposition) |
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추천시스템_CB_CF |
recommendation systems (content based and collaborative filtering) and matrix factorizations (non-negative matrix factorization, Cholesky decomposition) |
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추천시스템_MF_part1 |
recommendation systems (content based and collaborative filtering) and matrix factorizations (non-negative matrix factorization, Cholesky decomposition) |
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추천시스템_MF_part2 |
recommendation systems (content based and collaborative filtering) and matrix factorizations (non-negative matrix factorization, Cholesky decomposition) |
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11. |
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회귀 |
회귀분석 모델과 regularization (Ridge regression, Lasso regression) |
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회귀_ML_regularization |
회귀분석 모델과 regularization (Ridge regression, Lasso regression) |
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회귀_RBFN |
회귀분석 모델과 regularization (Ridge regression, Lasso regression) |
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12. |
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신경망 |
신경망의 역사와 학습 알고리즘 |
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신경망 |
신경망의 역사와 학습 알고리즘 |
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13. |
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최적화 |
최적화(gradient descent, Networn method, Trust-region) |
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최적화_gradient |
최적화(gradient descent, Networn method, Trust-region) |
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최적화_Newto |
최적화(gradient descent, Networn method, Trust-region) |
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14. |
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최적화/딥러닝 |
Optimization (Natural gradient 와 다른 최적화 관련 이슈들)/딥러닝 소개 |
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최적화/딥러닝_NG_part1 |
Optimization (Natural gradient 와 다른 최적화 관련 이슈들)/딥러닝 소개 |
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최적화/딥러닝_NG_part2 |
Optimization (Natural gradient 와 다른 최적화 관련 이슈들)/딥러닝 소개 |
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15. |
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딥러닝/순환신경망 |
딥러닝(representation learning)/RNNs(알고리즘 및 응용) |
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