인공지능

6주차 학습 일지 - CV 기초대회

사용한 기술 스택들: 10/24 월 학습한 것들: In competition, it is good to know the direction of where this is going - read the overview carefully Problem definition is important. - what is the problem that I need to solve? - What is the I/O of the problem? - Where is this solution being applied? Have the heart of solving the problem not increasing the rank. Domain understanding - Data Mining - Data Analysis - D..

부스트캠프 5주차 학습 일지 - Computer Vision Basics

사용한 기술 스택들: 10/18 화 학습한 것들: CNN visualization aims to see what's inside CNN(black box) - CNN visualization can be used to debug Filter visualization: can be used to show activation visualization of an image - it is hard to visualize like this after the first convolution layer Two focus: focus on data/focus on models Nearest neighbors in feature space: can look for clusters that are semantically ..

LeNet-5으로 더욱더 정확한 손글씨 분류기 만들기: MNIST-2

사용한 기술 스택들: LimePencil/MNIST: MNIST model trained using various models, implemented in PyTorch (github.com) GitHub - LimePencil/MNIST: MNIST model trained using various models, implemented in PyTorch MNIST model trained using various models, implemented in PyTorch - GitHub - LimePencil/MNIST: MNIST model trained using various models, implemented in PyTorch github.com 오늘은 저번 포스팅에 이어서 손글씨 분류기를 만들어..

MNIST 데이터셋 활용해서 간단한 딥러닝으로 손글씨 분류기 만들기: MNIST-1

사용한 기술 스택들: LimePencil/MNIST: MNIST model trained using various models, implemented in PyTorch (github.com) GitHub - LimePencil/MNIST: MNIST model trained using various models, implemented in PyTorch MNIST model trained using various models, implemented in PyTorch - GitHub - LimePencil/MNIST: MNIST model trained using various models, implemented in PyTorch github.com 오늘은 MNIST라는 데이터셋을 사용해서 손글씨 분..