Build an autograd backward graph by performing operations on PyTorch Autograd Tensors

AvgPool2D - Use the PyTorch AvgPool2D Module to incorporate average pooling into a PyTorch neural network

PyTorch Autograd - Use PyTorch's requires_grad to define a PyTorch Tensor with Autograd

BatchNorm2d - Use the PyTorch BatchNorm2d Module to accelerate Deep Network training by reducing internal covariate shift

PyTorch Tensor To List: Use PyTorch tolist() to convert a PyTorch Tensor into a Python list

Use the PyTorch view method to manage Tensor Shape within a Convolutional Neural Network

Construct A Custom PyTorch Model by creating your own custom PyTorch module by subclassing the PyTorch nn.Module class

Use PyTorch's nn.ReLU and add_module operations to define a ReLU layer

Use PyTorch nn.Sequential and PyTorch nn.Conv2d to define a convolutional layer in PyTorch

Use PyTorch's nn.Sequential and add_module operations to define a sequential neural network container

PyTorch item - Use PyTorch's item operation to convert a 0-dim PyTorch Tensor to a Python number

PyTorch Min - Use PyTorch's min operation to calculate the min of a PyTorch tensor

PyTorch Max - Use PyTorch's max operation to calculate the max of a PyTorch tensor

Find out which version of PyTorch is installed in your system by printing the PyTorch version

PyTorch Matrix Multiplication - Use torch.mm to do a PyTorch Dot Product

Use PyTorch's To List (tolist) operation to convert a PyTorch Tensor to a Python list

PyTorch List to Tensor - Use the PyTorch Tensor operation (torch.tensor) to convert a Python list object into a PyTorch Tensor

Augment the CIFAR10 Dataset Using the TorchVision RandomHorizontalFlip (transforms.RandomHorizontalFlip) and RandomCrop (transforms.RandomCrop) Transforms

Use Torchvision CenterCrop Transform (torchvision.transforms.CenterCrop) to do a rectangular crop of a PIL image

Use Torchvision CenterCrop Transform (torchvision.transforms.CenterCrop) to do a square crop of a PIL image

Get the shape of a PyTorch Tensor as a list of integers by using the PyTorch Shape operation and the Python List constructor

PyTorch Stack - Use the PyTorch Stack operation (torch.stack) to turn a list of PyTorch Tensors into one tensor

Check the TorchVision version by printing the version parameter

Use the Torchvision Transforms Parameter in the initialization function to apply transforms to PyTorch Torchvision Datasets during the data import process

Use Torchvision Transforms Normalize (transforms.Normalize) to normalize CIFAR10 dataset tensors using the mean and standard deviation of the dataset

Add a new dimension to the end of a PyTorch tensor by using None-style indexing

Add a new dimension to the middle of a PyTorch tensor by using None-style indexing

Add a new dimension to the beginning of a PyTorch tensor by using None-style indexing

PyTorch numel - Calculate the number of elements in a PyTorch Tensor by using the PyTorch numel operation

Create a PyTorch identity matrix by using the PyTorch eye operation

Use the PyTorch contiguous operation to move a PyTorch Tensor's data to a contiguous chunk of memory

Infer dimensions while reshaping a PyTorch tensor by using the PyTorch view operation

Flatten A PyTorch Tensor by using the PyTorch view operation

PyTorch View - how to use the PyTorch View (.view(...)) operation to reshape a PyTorch tensor

Transpose A Matrix In PyTorch by using the PyTorch T operation

Fill A PyTorch Tensor with a certain scalar by using the PyTorch fill operation

Tell PyTorch to do an in-place operation by using an underscore after an operation's name

Add two PyTorch Tensors together by using the PyTorch add operation

Specify PyTorch Tensor Maximum Value Threshold by using the PyTorch clamp operation

Specify PyTorch Tensor Minimum Value Threshold by using the PyTorch clamp operation

Use PyTorch clamp operation to clip PyTorch Tensor values to a specific range

Get the PyTorch Variable shape by using the PyTorch size operation

Calculate the biased standard deviation of all elements in a PyTorch Tensor by using the PyTorch std operation

Calculate the unbiased standard deviation of all elements in a PyTorch Tensor by using the PyTorch std operation

Calculate the power of each element in a PyTorch Tensor for a given exponent by using the PyTorch pow operation

Calculate the Sum of all elements in a tensor by using the PyTorch sum operation

Calculate the Mean value of all elements in a tensor by using the PyTorch mean operation

Convert CIFAR10 Dataset from PIL Images to PyTorch Tensors by Using PyTorch's ToTensor Operation

Check for element wise equality between two PyTorch tensors using the PyTorch eq equality comparison operation

Create a PyTorch Tensor full of ones so that each element is a ones using the PyTorch Ones operation

Create a PyTorch Tensor full of zeros so that each element is a zero using the PyTorch Zeros operation

Examine the MNIST dataset from PyTorch Torchvision using Python and PIL, the Python Imaging Library

PyTorch MNIST - Load the MNIST dataset from PyTorch Torchvision and split it into a train data set and a test data set

PyTorch CIFAR10 - Load CIFAR10 Dataset (torchvision.datasets.cifar10) from Torchvision and split into train and test data sets

PyTorch Element Wise Multiplication - Calculate the element wise multiplication to get the Hadamard Product

PyTorch Tensor Shape - Get the PyTorch Tensor size as a PyTorch Size object and as a list of integers

PyTorch Print Tensor - Print full tensor in PyTorch so that you can see all of the elements rather than just seeing the truncated or shortened version

PyTorch Variable To NumPy - Transform a PyTorch autograd Variable to a NumPy Multidimensional Array by extracting the PyTorch Tensor from the Variable and converting the Tensor to the NumPy array

PyTorch Tensor to NumPy - Convert a PyTorch tensor to a NumPy multidimensional array so that it retains the specific data type

PyTorch Variable - create a PyTorch Variable which wraps a PyTorch Tensor and records operations applied to it

PyTorch NumPy to tensor - Convert a NumPy Array into a PyTorch Tensor so that it retains the specific data type

PyTorch Concatenate - Use PyTorch cat to concatenate a list of PyTorch tensors along a given dimension

PyTorch change Tensor type - convert and change a PyTorch tensor to another type

PyTorch Tensor Type - print out the PyTorch tensor type without printing out the whole PyTorch tensor

torch create tensor - Create an uninitialized PyTorch Tensor and an initialized PyTorch Tensor

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