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IT 와 Social 이야기/ML-DL48

[edwith] 인공지능 및 기계학습 개론 I : C5. Support Vector Machine - 문일철교수 [LECTURE] 5.1. Decision Boundary with Margin : edwith - 신승재 www.edwith.org [LECTURE] 5.2. Maximizing the Margin : edwith - 신승재 www.edwith.org [LECTURE] 5.3. SVM with Matlab : edwith - 신승재 www.edwith.org [LECTURE] 5.4. Error Handling in SVM : edwith - 신승재 www.edwith.org [LECTURE] 5.5. Soft Margin with SVM : edwith - 신승재 www.edwith.org [LECTURE] 5.6. Rethinking of SVM : edwith - 신승재 www.edwith.org.. 2021. 3. 25.
[Idea Factory KAIST] 딥러닝 홀로서기 : #3.Lec - Linear Regression [발표자료] - 슬라이드1: https://hunkim.github.io/ml/lec2.pdf​ - 슬라이드2: https://hunkim.github.io/ml/lec3.pdf​ - 슬라이드3: https://docs.google.com/presentation/...​ - 자료 저장소 링크 : https://github.com/heartcored98/Stand...​ - 피드백 링크 : https://goo.gl/forms/EjHD7zJ6lvmh9thB2​ [Dingbro Crew] ★ 강의 - 조재영(whwodud9@kaist.ac.kr) ★ 촬영 - 김승수(seungsu0407@kaist.ac.kr) ★ 편집 - 김보성(kbs6473@kaist.ac.kr) ★ 디자인 - 황반석(hemistone@k.. 2021. 3. 24.
[edwith] 인공지능 및 기계학습 개론 I : C4. Logistic Regression - 문일철교수 [LECTURE] 4.1. Decision Boundary : edwith - 신승재 www.edwith.org [LECTURE] 4.2. Introduction to Logistic Regression : edwith - 신승재 www.edwith.org [LECTURE] 4.3. Logistic Regression Parameter Approximation 1 : edwith - 신승재 www.edwith.org [LECTURE] 4.4. Gradient Method : edwith - 신승재 www.edwith.org [LECTURE] 4.5. How Gradient method works : edwith - 신승재 www.edwith.org [LECTURE] 4.6. Logistic Regress.. 2021. 3. 24.
[edwith] 인공지능 및 기계학습 개론 I : C3. Naive Bayes Classifier - 문일철교수 [LECTURE] 3.1. Optimal Classification : edwith - 신승재 www.edwith.org [LECTURE] 3.2. Conditional Independence : edwith - 신승재 www.edwith.org [LECTURE] 3.3. Naive Bayes Classifier : edwith - 신승재 www.edwith.org [LECTURE] 3.4. Naive Bayes Classifier Application (Matlab Code) : edwith - 신승재 www.edwith.org - 출처: [edwith] 인공지능 및 기계학습 개론 I : C3. Naive Bayes Classifier - 문일철교수 2021. 3. 24.