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인공지능 및 기계학습 심화
KAIST 산업및시스템공학과 문일철 교수
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인공지능 및 기계학습 심화
인공지능 및 기계학습 심화
http://kooc.kaist.ac.kr/aiml-adv/lecture/21282/
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CHAPTER 1: Dirichlet Process
강좌 수강을 환영합니다! 여기부터 꼭 보고 넘어가세요-!
Dirichlet Process: Gaussian Mixture Model and Dirichlet Distribution Review
Dirichlet Process: Multinomial-Dirichlet Conjugate Relation
Dirichlet Process: Definition
Dirichlet Process: Stick-Breaking Construction
Dirichlet Process: Polya Urn Scheme
Dirichlet Process: Chinese Restaurant Process
Dirichlet Process: Random Process Review
Dirichlet Process: De Finetti's Theorem
Dirichlet Process: GMM Review
Dirichlet Process: Dirichlet Process Mixture Model (DPMM)
Dirichlet Process: DPMM Implementation
Dirichlet Process: DPMM Sampling Process
Dirichlet Process: Problem of Separate Prior
Dirichlet Process: Atom Sharing
Dirichlet Process: HDP with Stick-Breaking Construction
Dirichlet Process: HDP with Chinese Restaurant Franchise
Dirichlet Process: Quiz
CHAPTER 2: Gaussian Process
Gaussian Process: Introduction (1)
Gaussian Process: Introduction (2)
Gaussian Process: Introduction (3)
Gaussian Process: Mapping Function Review
Gaussian Process: GP Regression (1)
Gaussian Process: Kernel Function Review
Gaussian Process: GP Regression (2)
Gaussian Process: GP Regression (3)
Gaussian Process: GP Regression (4)
Gaussian Process: GP Regression (5)
Gaussian Process: GP Regression (6)
Gaussian Process: GP Regression (7)
Gaussian Process: GP Regression (8)
Gaussian Process: GP Regression (9)
Gaussian Process: Hyper-parameter Learning (1)
Gaussian Process: Hyper-parameter Learning (2)
Gaussian Process: GP Classifier
Gaussian Process: Bayesian Optimization with GP
Gaussian Process: Acquisition Function (1)
Gaussian Process: Acquisition Function (2)
Gaussian Process: Bayesian Optimization Result
Gaussian Process: Quiz
CHAPTER 3: Variational Inference
Variational Inference: Variational Transform
Variational Inference: Variational Transform of Probability Density Function
Variational Inference: Theory (1)
Variational Inference: Theory (2)
Variational Inference: Theory (3)
Variational Inference: Simple Example Model (1)
Variational Inference: Simple Example Model (2)
Variational Inference: Simple Example Model (3)
Variational Inference: Simple Example Model (4)
Variational Inference: LDA Review
Variational Inference: LDA (1)
Variational Inference: Dirichlet Distribution and Exponential Family Review
Variational Inference: LDA (2)
Variational Inference: LDA (3)
Variational Inference: LDA (4)
Variational Inference: LDA (5)
Variational Inference: LDA (6)
Variational Inference: LDA (7)
Variational Inference: LDA Implementation
Variational Inference: LDA Evaluation
Variational Inference: Quiz
CHAPTER 4: Neural Network 1
Artificial Neural Network: Introduction
Artificial Neural Network: Activation Functions
Artificial Neural Network: XOR Problem
Artificial Neural Network: Structure of NN
Artificial Neural Network: Example of Training NN (1)
Artificial Neural Network: Example of Training NN (2)
Artificial Neural Network: Example of Training NN (3)
Artificial Neural Network: Training Techniques and Problems of NN
Artificial Neural Network: Quiz
Final Exam
Final Exam
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Errata
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Dirichlet Process: DPMM Sampling Process
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Dirichlet Process: DPMM Sampling Process - 문일철
Dirichlet Process: DPMM Sampling Process - 문일철
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Dirichlet Process: DPMM Implementation
Dirichlet Process: Problem of Separate Prior
