Day72_Ai(8)_Pm
CNN 또다른 알고리즘CNNEx1import torchimport torch.nn as nninputs = torch.Tensor(1,1,28,28)#batch, channel, height, weightprint(inputs.shape)#padding, strideconv1 = nn.Conv2d(in_channels=1, out_channels=32, kernel_size=3, padding=1, stride=1)print(conv1)conv2 = nn.Conv2d(32,64,3,padding=1)print(conv2)pool = nn.MaxPool2d(kernel_size=2)print(pool)print()output = conv1(inputs )print(output.size())print()ou..
2025. 11. 5.
Day70_Ai(6)_Pm
perceptronEximport torchimport torch.nn as nnimport torch.optim as optimtorch.manual_seed(777)x_data = torch.FloatTensor([[0,0],[0,1],[1,0],[1,1]])y_data = torch.FloatTensor([[0],[1],[1],[1]])model = nn.Sequential( #층층이 객체생성할때 심플하게 만들기 위해 nn.Linear(2,2), nn.Sigmoid(), nn.Linear(2,1), nn.Sigmoid())loss_func = nn.BCELoss()optimizer = optim.SGD(model.parameters(), lr=1)for ..
2025. 11. 3.
Day67_Ai(5)_Pm
import torchx_train = torch.FloatTensor([[73,80,75], [93,88,93], [89,91,80], [96,98,100], [73,65,70]])# x1_train = torch.FloatTensor([[73],[93],[89],[96],[73]])# x2_train = torch.FloatTensor([[80],[88],[91],[98],[65]])# x3_train = torch.FloatTensor([[75],[92],[80],[100],[70]])y_train =..
2025. 10. 31.