로컬 데이터를 불러와 전처리시 필요한 내용이다. Load Packages 12345678910import osfrom glob import globimport numpy as npimport tensorflow as tffrom PIL import Imageimport matplotlib.pyplot as plt%matplotlib inline 12345
딥러닝 교육자료 딥러닝을 배우기 위한 강의 사이트와 책을 정리하였다. 교육 사이트 프로그래머스 - https://programmers.co.kr/ 에드윗 - https://www.edwith.org/ 입문 강의 파이썬 입문 - https://programmers.co.kr/learn/courses/2 딥러닝 입문(Tensorflow) - http
TensorFlow 2.0 123import tensorflow as tffrom tensorflow.keras import layersfrom tensorflow.keras import datasets Hyperparameter 1234567batch_size = 64learning_rate = 0.001dropout_rate = 0.7input_sh
Load Packages 12import numpy as npimport torch Basic PyTorch 기초 사용법 1234nums = torch.arange(9)nums.shapenums.numpy()nums.reshape(3, 3) 1234randoms = torch.rand((3, 3))zeros = torch.zeros((3, 3))ones
Load Packages 1234import tensorflow as tffrom tensorflow.keras import layersfrom tensorflow.keras import datasets Build Model 123456789101112131415161718192021222324252627input_shape = (28, 28, 1)nu
TensorFlow 공식 홈페이지에서 설명하는 Expert 버전을 사용해본다. Load Packages 1234import tensorflow as tffrom tensorflow.keras import layersfrom tensorflow.keras import datasets 학습 과정 돌아보기 Build Model 12345678910111
Load Packages 1234import tensorflow as tffrom tensorflow.keras import layersfrom tensorflow.keras import datasets 학습 과정 돌아보기 Prepare MNIST Datset 1(train_x, train_y), (test_x, test_y) = datasets.m
Load Packages 12345import tensorflow as tfimport osimport matplotlib.pyplot as plt%matplotlib inline Input Image 1234567891011from tensorflow.keras import datasets(train_x, train_y), (test_x, test_y
Load Packages 123456import numpy as npimport matplotlib.pyplot as pltimport tensorflow as tf%matplotlib inline 데이터 불러오기 TensorFlow 에서 제공해주는 데이터셋(MNIST) 예제 불러오기다. 12345678from tensorflow.keras import
Load Packages 12import numpy as npimport tensorflow as tf Tensor 생성 list -> Tensor 1234tf.constant([1, 2, 3])# Out<tf.Tensor: shape=(3,), dtype=int32, numpy=array([1, 2, 3])> tuple -> Te