文件名称：Pytorch_tutorial
文件大小：53.35MB
文件格式：ZIP
更新时间：2024-03-05 16:37:04
JupyterNotebook
Pytorch_tutorial Pytorch_tutorial 我们的目标 。근를근사하는하는다。 。의의하는。한한한한。。 함수함수를를다를를다。 。된된다。 01 torch.FloatTensor（x）：32位元的摘要 torch.LongTensor（x）：정수를다，索引索引많이많 torch.ByteTensor（x）：0，1쓰이며，torch.BooleanTensor（x）로） torch.from_numpy（x）：numpy浏览器 torch.numpy（）：张量numpy로변화 02. tensor_operations 张量사칙연산：元素明智연산수행 明智的元素操作：연산이각요소에로이루어진다는는 a = torch . FloatTensor ([[ 1 , 2 ], [ 3 , 4 ]]) b =
【文件预览】：
Pytorch_tutorial-main
----07-dnn_1()
--------.ipynb_checkpoints()
--------10-06-dnn_regression.ipynb(77KB)
----README.md(5KB)
----09-optimizer()
--------12-05-adam.ipynb(259KB)
--------.ipynb_checkpoints()
----10-prevent_overfitting()
--------.ipynb_checkpoints()
--------13-03-split_dataset.ipynb(262KB)
----12-regularizations()
--------15-06-regularizations.ipynb(84KB)
--------.ipynb_checkpoints()
----04-gradient_descent()
--------07-06-gradient_descent.ipynb(7KB)
--------.ipynb_checkpoints()
--------07-05-auto_grad.ipynb(5KB)
----03-loss_function()
--------.ipynb_checkpoints()
--------06-02-mse.ipynb(4KB)
----08-sgd()
--------.ipynb_checkpoints()
--------11-04-sgd.ipynb(1.83MB)
----05-linear_regression()
--------.ipynb_checkpoints()
--------08-03-linear_regression.ipynb(1.91MB)
----06-logistic_regression()
--------.ipynb_checkpoints()
--------09-06-logistic_regression.ipynb(3.27MB)
--------09-02-activation_functions.ipynb(27KB)
----11-dnn_2()
--------14-03-binary_classification.ipynb(100KB)
--------.ipynb_checkpoints()
--------14-07-classification.ipynb(78KB)
----01_pytorch_tutorials()
--------04-08-tensor_useful_methods.ipynb(10KB)
--------04-06-tensor_manipulations.ipynb(7KB)
--------04-04-tensor.ipynb(7KB)
--------.ipynb_checkpoints()
--------04-05-tensor_operations.ipynb(11KB)
--------04-07-tensor_slicing_and_concat.ipynb(10KB)
--------04-02-hello_pytorch.ipynb(2KB)
----13-practical_exercise()
--------train.py(2KB)
--------trainer.py(3KB)
--------.ipynb_checkpoints()
--------utils.py(1KB)
--------model.pth(6.41MB)
--------model.py(2KB)
--------predict.ipynb(415KB)
----02-linear_layer()
--------05-02-matrix_multiplication.ipynb(3KB)
--------.ipynb_checkpoints()
--------05-04-linear_layer.ipynb(10KB)
--------05-05-use_gpu.ipynb(10KB)
----data()
--------MNIST()