Category: Machine-Learning
2016
Machine learning 스터디 (10) PAC Learning & Statistical Learning Theory
내 멋대로 정리해보는 Machine Learning. PAC Learning & Statistical Learning Theory
Machine-Learning, Machine-Learning-Study
Practical Bayesian Optimization of Machine Learning Algorithms (NIPS 2012)
NIPS 2012에 발표된 Practical Bayesian Optimization of Machine Learning Algorithms 정리
Machine-Learning, Paper-Review, Research
AlphaGo의 알고리즘과 모델
Google Deep Mind에서 2016년 Nature에 발표한 matering the Game of Go with Deep Neural Network and Tree Search 정리. 이 논문은 바둑 프로그램 AlphaGo에 대한 논문이다.
Deep-Learning, Machine-Learning, Neural-Network, Paper-Review, Reinforcement-Learning, Research
Machine learning 스터디 (20-1) Multi-armed Bandit
내 멋대로 정리해보는 Machine Learning. Multi-armed Bandit
Machine-Learning, Machine-Learning-Study
Machine learning 스터디 (17-1) Recommendation System with Implicit Feedback
내 멋대로 정리해보는 Machine Learning. Recommendation System with Implicit Feedback
Machine-Learning, Machine-Learning-Study
Machine learning 스터디 (17) Recommendation System (Matrix Completion)
내 멋대로 정리해보는 Machine Learning. Recommendation System
Machine-Learning, Machine-Learning-Study
2015
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention (ICML2015)
ICML 2015에 발표된 Show, Attend and Tell: Neural Image Caption Generation with Visual Attention 정리
Deep-Learning, Machine-Learning, Neural-Network, Paper-Review, Reinforcement-Learning, Research
고흐의 그림을 따라그리는 Neural Network, A Neural Algorithm of Artistic Style (2015)
2015년에 arXiv에 upload된 A Neural Algorithm of Artistic Style 논문 리뷰
Deep-Learning, Machine-Learning, Neural-Network, Paper-Review, Research
The Basic Principles in Deep Neural Networks
2014/06/16 조경현 박사님의 Deep learning seminar 요약 내용
Machine-Learning, Neural-Network, Seminar
Kaggle competition - Poker rule induction
Kaggle competition Poker rule induction 문제 해결기
Development, Kaggle, Machine-Learning
Machine learning 스터디 (20) Reinforcement Learning
내 멋대로 정리해보는 Machine Learning. Reinforcement Learning
Machine-Learning, Machine-Learning-Study, Reinforcement-Learning
Machine learning 스터디 (19) Deep Learning - RBM, DBN, CNN
내 멋대로 정리해보는 Machine Learning. Deep Learning
Deep-Learning, Machine-Learning, Machine-Learning-Study, Neural-Network
Recurrent Models of Visual Attention (NIPS 2014)
Google Deep Mind에서 NIPS 2014에 발표한 Recurrent Models of Visual Attention 정리
Deep-Learning, Machine-Learning, Neural-Network, Paper-Review, Reinforcement-Learning, Research
Playing Atari with Deep Reinforcement Learning (NIPS 2013)
Google Deep Mind에서 NIPS 2013에 발표한 Playing Atari with Deep Reinforcement Learning 정리
Deep-Learning, Machine-Learning, Neural-Network, Paper-Review, Reinforcement-Learning, Research
Recurrent Neural Network Regularization
ArXiv에 업로드되어있는 Recurrent Neural Network Regularization 정리
Deep-Learning, Machine-Learning, Neural-Network, Paper-Review, Research
Machine learning 스터디 (18) Neural Network Introduction
내 멋대로 정리해보는 Machine Learning. Neural Network Introduction
Deep-Learning, Machine-Learning, Machine-Learning-Study, Neural-Network
Batch Normalization (ICML 2015)
Google이 작성한 현재 ImageNet classification competition state-of-art이고 ICML 2015에 발표된 Batch Normalization 정리
Deep-Learning, Machine-Learning, Neural-Network, Paper-Review, Research
Machine learning 스터디 (16) Dimensionality Reduction (PCA, LDA)
내 멋대로 정리해보는 Machine Learning. Dimensionality Reduction
Machine-Learning, Machine-Learning-Study
Machine learning 스터디 (14) EM algorithm
내 멋대로 정리해보는 Machine Learning. EM algorithm
Machine-Learning, Machine-Learning-Study
Machine learning 스터디 (13) Clustering (K-means, Gaussian Mixture Model)
내 멋대로 정리해보는 Machine Learning. Clustering
Machine-Learning, Machine-Learning-Study
Machine learning 스터디 (8) Classification Introduction (Decision Tree, Naïve Bayes, KNN)
내 멋대로 정리해보는 Machine Learning. Classification
Machine-Learning, Machine-Learning-Study
2014
Machine learning 스터디 (7) Convex Optimization
내 멋대로 정리해보는 Machine Learning. Convex Optimization
Machine-Learning, Machine-Learning-Study
Machine learning 스터디 (6) Information Theory
내 멋대로 정리해보는 Machine Learning. Information Theory
Machine-Learning, Machine-Learning-Study
Machine learning 스터디 (5) Decision Theory
내 멋대로 정리해보는 Machine Learning. Decision Theory
Machine-Learning, Machine-Learning-Study
Machine learning 스터디 (4) Algorithm
내 멋대로 정리해보는 Machine Learning. Algorithm
Machine-Learning, Machine-Learning-Study
Machine learning 스터디 (3) Overfitting
내 멋대로 정리해보는 Machine Learning. Overfitting, Regularization, Model Selection, Curse of dimension 등
Machine-Learning, Machine-Learning-Study
Machine learning 스터디 (2) Probability Theory
내 멋대로 정리해보는 Machine Learning. 기본적인 Background Knowledge 중 하나인 Probability Theory
Machine-Learning, Machine-Learning-Study
Machine learning 스터디 (1) Machine Learning이란?
내 멋대로 정리해보는 Machine Learning. 간단한 Introduction
Machine-Learning, Machine-Learning-Study
2014 ICML 후기
2014년 6월 21일부터 26일까지 있었던 ICML 후기
Conference, ICML, ICML2014, Machine-Learning
Coursera Neural Networks for Machine Learning Week4 & 5 - Applications
Geoffrey Hinton 교수가 2012년 Coursera에서 강의 한 Neural Networks for Machine Learning 강의 4주차와 5주차 요약글
Cousera, Cousera-NN, Lecture, Machine-Learning, Neural-Network
Coursera Neural Networks for Machine Learning Week3 - Backpropagation
Geoffrey Hinton 교수가 2012년 Coursera에서 강의 한 Neural Networks for Machine Learning 강의 3주차 요약글
Cousera, Cousera-NN, Lecture, Machine-Learning, Neural-Network
Coursera Neural Networks for Machine Learning Week2 - Perceptron
Geoffrey Hinton 교수가 2012년 Coursera에서 강의 한 Neural Networks for Machine Learning 강의 2주차 요약글
Cousera, Cousera-NN, Lecture, Machine-Learning, Neural-Network
Coursera Neural Networks for Machine Learning Week1 - Neural Network and Machine Learning
Geoffrey Hinton 교수가 2012년 Coursera에서 강의 한 Neural Networks for Machine Learning 강의 첫 주차 요약글
Cousera, Cousera-NN, Lecture, Machine-Learning, Neural-Network
LMNN(Large Margin Nearest Neighbors) (NIPS 2006) LMCA(Large Margin Component Anaylsis) (NIPS 2007)
NIPS 2006에 발표된 LMNN, 그리고 2007년에 발표된 LMCA 정리
Machine-Learning, Paper-Review, Research
Distance Metric Learning
Distance Metric Learning에 대해 설명하는 글
Machine-Learning, Research
2013
인터넷 속의 수학 - How does Netflix recommend movies? (2/2)
단기강좌 인터넷 속의 수학에서 둘째날 강의인 'How does Netflix recommend movies?' 의 요약글 2 중 2
Big-Data, Lecture, Machine-Learning, Math-in-Internet
인터넷 속의 수학 - How does Netflix recommend movies? (1/2)
단기강좌 인터넷 속의 수학에서 둘째날 강의인 'How does Netflix recommend movies?' 의 요약글 2 중 1
Big-Data, Lecture, Machine-Learning, Math-in-Internet
Machine Learning Week2 - Linear Regression
Stanford Andrew Ng교수의 Coursera 강의 중 Linear Regession 부분을 요약한 글
Machine-Learning
Andrew Ng 교수의 Machine Learning강의 수강 완료
Stanford Andrew Ng교수의 Coursera 강의 수강 완료 후 짤막한 소감
Machine-Learning
Machine Learning Week1 - What is Machine Learning
Stanford Andrew Ng교수의 Coursera 강의 첫 주차를 듣고 요약한 글
Machine-Learning
2016
Machine learning 스터디 (10) PAC Learning & Statistical Learning Theory
내 멋대로 정리해보는 Machine Learning. PAC Learning & Statistical Learning Theory
Practical Bayesian Optimization of Machine Learning Algorithms (NIPS 2012)
NIPS 2012에 발표된 Practical Bayesian Optimization of Machine Learning Algorithms 정리
AlphaGo의 알고리즘과 모델
Google Deep Mind에서 2016년 Nature에 발표한 matering the Game of Go with Deep Neural Network and Tree Search 정리. 이 논문은 바둑 프로그램 AlphaGo에 대한 논문이다.
Machine learning 스터디 (20-1) Multi-armed Bandit
내 멋대로 정리해보는 Machine Learning. Multi-armed Bandit
Machine learning 스터디 (17-1) Recommendation System with Implicit Feedback
내 멋대로 정리해보는 Machine Learning. Recommendation System with Implicit Feedback
Machine learning 스터디 (17) Recommendation System (Matrix Completion)
내 멋대로 정리해보는 Machine Learning. Recommendation System
2015
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention (ICML2015)
ICML 2015에 발표된 Show, Attend and Tell: Neural Image Caption Generation with Visual Attention 정리
고흐의 그림을 따라그리는 Neural Network, A Neural Algorithm of Artistic Style (2015)
2015년에 arXiv에 upload된 A Neural Algorithm of Artistic Style 논문 리뷰
The Basic Principles in Deep Neural Networks
2014/06/16 조경현 박사님의 Deep learning seminar 요약 내용
Kaggle competition - Poker rule induction
Kaggle competition Poker rule induction 문제 해결기
Machine learning 스터디 (20) Reinforcement Learning
내 멋대로 정리해보는 Machine Learning. Reinforcement Learning
Machine learning 스터디 (19) Deep Learning - RBM, DBN, CNN
내 멋대로 정리해보는 Machine Learning. Deep Learning
Recurrent Models of Visual Attention (NIPS 2014)
Google Deep Mind에서 NIPS 2014에 발표한 Recurrent Models of Visual Attention 정리
Playing Atari with Deep Reinforcement Learning (NIPS 2013)
Google Deep Mind에서 NIPS 2013에 발표한 Playing Atari with Deep Reinforcement Learning 정리
Recurrent Neural Network Regularization
ArXiv에 업로드되어있는 Recurrent Neural Network Regularization 정리
Machine learning 스터디 (18) Neural Network Introduction
내 멋대로 정리해보는 Machine Learning. Neural Network Introduction
Batch Normalization (ICML 2015)
Google이 작성한 현재 ImageNet classification competition state-of-art이고 ICML 2015에 발표된 Batch Normalization 정리
Machine learning 스터디 (16) Dimensionality Reduction (PCA, LDA)
내 멋대로 정리해보는 Machine Learning. Dimensionality Reduction
Machine learning 스터디 (14) EM algorithm
내 멋대로 정리해보는 Machine Learning. EM algorithm
Machine learning 스터디 (13) Clustering (K-means, Gaussian Mixture Model)
내 멋대로 정리해보는 Machine Learning. Clustering
Machine learning 스터디 (8) Classification Introduction (Decision Tree, Naïve Bayes, KNN)
내 멋대로 정리해보는 Machine Learning. Classification
2014
Machine learning 스터디 (7) Convex Optimization
내 멋대로 정리해보는 Machine Learning. Convex Optimization
Machine learning 스터디 (6) Information Theory
내 멋대로 정리해보는 Machine Learning. Information Theory
Machine learning 스터디 (5) Decision Theory
내 멋대로 정리해보는 Machine Learning. Decision Theory
Machine learning 스터디 (4) Algorithm
내 멋대로 정리해보는 Machine Learning. Algorithm
Machine learning 스터디 (3) Overfitting
내 멋대로 정리해보는 Machine Learning. Overfitting, Regularization, Model Selection, Curse of dimension 등
Machine learning 스터디 (2) Probability Theory
내 멋대로 정리해보는 Machine Learning. 기본적인 Background Knowledge 중 하나인 Probability Theory
Machine learning 스터디 (1) Machine Learning이란?
내 멋대로 정리해보는 Machine Learning. 간단한 Introduction
2014 ICML 후기
2014년 6월 21일부터 26일까지 있었던 ICML 후기
Coursera Neural Networks for Machine Learning Week4 & 5 - Applications
Geoffrey Hinton 교수가 2012년 Coursera에서 강의 한 Neural Networks for Machine Learning 강의 4주차와 5주차 요약글
Coursera Neural Networks for Machine Learning Week3 - Backpropagation
Geoffrey Hinton 교수가 2012년 Coursera에서 강의 한 Neural Networks for Machine Learning 강의 3주차 요약글
Coursera Neural Networks for Machine Learning Week2 - Perceptron
Geoffrey Hinton 교수가 2012년 Coursera에서 강의 한 Neural Networks for Machine Learning 강의 2주차 요약글
Coursera Neural Networks for Machine Learning Week1 - Neural Network and Machine Learning
Geoffrey Hinton 교수가 2012년 Coursera에서 강의 한 Neural Networks for Machine Learning 강의 첫 주차 요약글
LMNN(Large Margin Nearest Neighbors) (NIPS 2006) LMCA(Large Margin Component Anaylsis) (NIPS 2007)
NIPS 2006에 발표된 LMNN, 그리고 2007년에 발표된 LMCA 정리
Distance Metric Learning
Distance Metric Learning에 대해 설명하는 글
2013
인터넷 속의 수학 - How does Netflix recommend movies? (2/2)
단기강좌 인터넷 속의 수학에서 둘째날 강의인 'How does Netflix recommend movies?' 의 요약글 2 중 2
인터넷 속의 수학 - How does Netflix recommend movies? (1/2)
단기강좌 인터넷 속의 수학에서 둘째날 강의인 'How does Netflix recommend movies?' 의 요약글 2 중 1
Machine Learning Week2 - Linear Regression
Stanford Andrew Ng교수의 Coursera 강의 중 Linear Regession 부분을 요약한 글
Andrew Ng 교수의 Machine Learning강의 수강 완료
Stanford Andrew Ng교수의 Coursera 강의 수강 완료 후 짤막한 소감
Machine Learning Week1 - What is Machine Learning
Stanford Andrew Ng교수의 Coursera 강의 첫 주차를 듣고 요약한 글