AI11 pca관련 링크 https://www.youtube.com/playlist?list=PLLViszK5qws1SUpVeEiGxHpjnJC-_ZzMy PCA www.youtube.com 2023. 1. 8. 학습 필요 링크 모음 ASCII.jp：ロードマップでわかる！当世プロセッサー事情 ロードマップでわかる！当世プロセッサー事情 多くの新製品が世に送り出されるプロセッサーの世界。テクニカルライターの大原雄介氏による本連載では、CPUやGPUなどコンピューターの中核となるプロセッサーのロードマップを軸に、そ ascii.jp 2022. 12. 12. CNN https://www.youtube.com/watch?v=UximUEjPQco https://www.youtube.com/watch?v=dqa2UGUH-48&t=0s https://www.youtube.com/watch?v=05qlCP-xL9Y 2021. 12. 15. semantic segmentation https://www.youtube.com/watch?v=Eu7EKQ--Rvk&t=3s 2021. 12. 15. 논문 리뷰 논문으로 짚어보는 딥러닝의 맥 > 4가지 CNN 살펴보기: AlexNET, VGG, GoogLeNet, ResNet : edwith [LECTURE] 4가지 CNN 살펴보기: AlexNET, VGG, GoogLeNet, ResNet : edwith 학습목표 최신 CNN 구조 중 AlexNet, VGG, GoogLeNet, ResNet 이렇게 4가지 구조에 대해서 알아보겠습니다. 위 4가지 구조들은 일반적으로 딥러닝의 유명한 ... - 커넥트재단 www.edwith.org [논문 리뷰] Deep Residual Learning for Image Recognition - ResNet(1) (tistory.com) [논문 리뷰] Deep Residual Learning for Image Recognition .. 2021. 12. 7. 딥러닝 개론. 시그모이드 함수와 zigzag 문제 neural networks - Why are non zero-centered activation functions a problem in backpropagation? - Cross Validated (stackexchange.com) Why are non zero-centered activation functions a problem in backpropagation? I read here the following: Sigmoid outputs are not zero-centered. This is undesirable since neurons in later layers of processing in a Neural Network (more on this soon) would be receiving.. 2021. 11. 19. 선행대수-인공지능을 위한- 스탠포드-강의록 등 (2) ENGR108: Introduction to Applied Linear Algebra—Vectors, Matrices, and Least Squares - YouTube ENGR108: Introduction to Applied Linear Algebra—Vectors, Matrices, and Least Squares Lectures by Professor Stephen Boyd, Stanford University. Introduction to applied linear algebra with emphasis on applications. Topics include: Vectors, norm,... www.youtube.com 1. 강의 소개 - (2) Stanford ENGR108: Intr.. 2021. 9. 20. fmincon 연습 Constrained Optimization in Matlab (colostate.edu) Constrained Optimization in Matlab For constrained minimization of an objective function f(x) (for maximization use -f), Matlab provides the command fmincon. The objective function must be coded in a function file in the same manner as for fminunc. In these notes this file will be called ob www.math.colostate.edu 2021. 9. 19. 회귀분석 연습 프로그램 from google.colab import drive drive.mount('/content/gdrive') import tensorflow as tf import numpy as np import matplotlib.pyplot as plt import keras from keras.models import Sequential from keras.layers.core import Dense #from keras.optimizers import RMSprop from tensorflow.keras.optimizers import RMSprop np.random.seed(7) print('tensorflow version: ', tf.__version__) print('keras version: ', k.. 2021. 9. 18. minst 관련 연습 소프트웨어 from keras.datasets import mnist from keras.utils import np_utils from keras.models import Sequential from keras.layers import Dense (X_train, Y_train), (X_validation, Y_validation) = mnist.load_data() X_train = X_train.reshape(X_train.shape[0], 784).astype('float64') / 255 X_validation = X_validation.reshape(X_validation.shape[0], 784).astype('float64') / 255 Y_train = np_utils.to_categorical(Y.. 2021. 9. 17. 이전 1 2 다음
