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CS231n
팀 주제
CNN
팀원
아보카도
C
NN
소개
”
C
NN
SEED
is all
AND END
all.
”
아보카도 씨만큼 단단한
C
NN
은 중요하다.
작성자
강다은(따쯔) |
중앙대 공공인재학부
김정국(Uni) |
고려대 통계학과
이기은(끼니) |
서울대 언론정보학과
참고 강의
Stanford University CS231n
Lecture 1 | Introduction to Convolutional Neural Networks for Visual Recognition
Lecture 1 gives an introduction to the field of computer vision, discussing its history and key challenges. We emphasize that computer vision encompasses a w...
아보카도
C
NN
Wikipedia
Lecture 01 |
Introduction to CNN for Visual Recognition
Lecture 02 |
Image Classification
Image Classification
Nearest Neighbor
K-Nearest Neighbors(KNN)
L1 거리 (맨해튼 거리)
L2 거리 (유클리디언 거리)
Lecture 03 |
Loss Functions and Optimization
Loss Function
Optimization
Lecture 04 |
Introduction to Neural Networks
Computational Graph
Backpropagation (역전파)
Neural Network
Lecture 05 |
Convolutional Neural Networks
Neural Networks의 역사
Convolutional Neural Networks의 역사
ConvNet의 작동원리
Lecture 06 |
Training Neural Networks I
Activation Functions
Data Preprocessing
Weight Initialization
Batch Normalization
Babysitting the Learning Process
Hyperparameter Optimization
Lecture 07 |
Training Neural Networks II
Optimization (최적화)
Regularization (정규화)
Transfer Learning
기타 문서
Multiclass SVM Loss
Softmax
Gradient Descent