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Make A Simple PyTorch Autograd Computational Graph

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

3:49

How to incorporate average pooling into a pytorch neural network 280x158

AvgPool2D: How to Incorporate Average pooling into a PyTorch Neural Network

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

2:10

Define a pytorch tensor with autograd 280x158

PyTorch Autograd: Define A PyTorch Tensor With Autograd

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

1:55

How to use the batchnorm2d module in pytorch 280x158

BatchNorm2d: How to use the BatchNorm2d Module in PyTorch

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

2:02

PyTorch Tensor To List: Convert a PyTorch Tensor To A Python List

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

2:58

How To Use The view Method To Manage Tensor Shape In PyTorch

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

3:29

Calculate TensorFlow Median Value

tf.contrib.distributions.percentile - Calculate TensorFlow Median Value using the percentile distribution and the interpolation methods

1:32

How to Subclass The nn.Module Class in PyTorch

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

1:54

How To Define A ReLU Layer In PyTorch

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

2:30

How To Define A Convolutional Layer In PyTorch

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

3:10

tf.transpose: Transpose A Matrix in TensorFlow

tf.transpose - Use TensorFlow's transpose operation to transpose a TensorFlow matrix tensor

2:23

How To Define A Sequential Neural Network Container In PyTorch

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

1:38

Print and check tensorflow tensor type 280x158

tf.dtype: Print And Check TensorFlow Tensor Type

tf.dtype - Use TensorFlow's dtype operation to print and check a TensorFlow's Tensor data type

2:21

Convert a 0 dim pytorch tensor to a python number 280x158

PyTorch item: Convert A 0-dim PyTorch Tensor To A Python Number

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

1:50

Calculate min of a pytorch tensor 280x158

PyTorch Min: Get Minimum Value Of A PyTorch Tensor

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

1:55

Calculate max of a pytorch tensor 280x158

PyTorch Max: Get Maximum Value Of A PyTorch Tensor

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

1:56

Print PyTorch Version

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

0:59

PyTorch Matrix Multiplication: How To Do A PyTorch Dot Product

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

3:26

Get minimum value of a tensorflow tensor 280x158

tf.reduce_min: Get Minimum Value Of A TensorFlow Tensor

tf.reduce_min - Use TensorFlow's reduce_min operation to get the minimum value of a TensorFlow Tensor

1:42

Create tensorflow tensor with random uniform distribution 280x158

tf.random_uniform: Create TensorFlow Tensor With Random Uniform Distribution

Use TensorFlow's random_uniform operation to create a TensorFlow Tensor with a random uniform distribution

2:33

Convert a pytorch tensor to a list 280x158

PyTorch Tensor To List: How To Convert A PyTorch Tensor To A List

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

2:08

Flatten A TensorFlow Tensor

Use the TensorFlow reshape operation to flatten a TensorFlow Tensor

3:17

Print TensorFlow Tensor Shape

Use the TensorFlow get_shape operation to print the static shape of a TensorFlow tensor as a list

2:35

Print TensorFlow Version

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

1:16

List All Tensor Names In A TensorFlow Graph

Use the TensorFlow Get Operations Operation to list all Tensor names in a TensorFlow graph

4:40

PyTorch List to Tensor: Convert A Python List To A PyTorch Tensor

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

2:01

Augment the CIFAR10 Dataset Using the RandomHorizontalFlip and RandomCrop Transforms

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

3:20

Use Torchvision CenterCrop Transform To Do A Rectangular Crop Of A PIL Image

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

3:33

Use Torchvision CenterCrop Transform To Do A Square Crop Of A PIL Image

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

3:40

Convert List To TensorFlow Tensor

Convert a python list into a TensorFlow Tensor using the TensorFlow convert_to_tensor functionality

2:21

Get The Shape Of A PyTorch Tensor As A List Of Integers

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

2:28

Turn a list of pytorch tensors into one tensor 280x158

PyTorch Stack: Turn A List Of PyTorch Tensors Into One Tensor

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

3:03

Check Torchvision Version

Check the TorchVision version by printing the version parameter

0:26

Create TensorFlow Name Scopes For TensorBoard

Use TensorFlow Name Scopes (tf.name_scope) to group graph nodes in the TensorBoard web service so that your graph visualization is legible

6:04

Visualize TensorFlow Graph In TensorBoard

Use TensorFlow Summary File Writer (tf.summary.FileWriter) and the TensorBoard command line unitility to visualize a TensorFlow Graph in the TensorBoard web service

4:23

Apply Transforms To PyTorch Torchvision Datasets

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

1:51

Launch TensorFlow TensorBoard

Use the TensorBoard command line utility to launch the TensorFlow TensorBoard web service

1:23

Normalize CIFAR10 Dataset Tensor

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

1:42

Create TensorFlow Summary File Writer For TensorBoard

Use TensorFlow Summary File Writer (tf.summary.FileWriter) to create a TensorFlow Summary Event File for TensorBoard

4:17

Add A New Dimension To The End Of A Tensor In PyTorch

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

2:10

Add A New Dimension To The Middle Of A Tensor In PyTorch

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

2:12

Add A New Dimension To The Beginning Of A Tensor In PyTorch

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

1:37

Calculate the number of elements in a pytorch tensor 280x158

PyTorch numel: Calculate The Number Of Elements In A PyTorch Tensor

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

1:22

Create A PyTorch Identity Matrix

Create a PyTorch identity matrix by using the PyTorch eye operation

1:03

Move PyTorch Tensor Data To A Contiguous Chunk Of Memory

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

5:59

Infer Dimensions While Reshaping A PyTorch Tensor

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

4:00

Flatten A PyTorch Tensor

Flatten A PyTorch Tensor by using the PyTorch view operation

2:22

PyTorch View: Reshape A PyTorch Tensor

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

3:34

Fill a pytorch tensor with a certain scalar 280x158

Transpose A Matrix In PyTorch

Transpose A Matrix In PyTorch by using the PyTorch T operation

1:59

Fill A PyTorch Tensor With A Certain Scalar

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

2:09

Tell PyTorch To Do An In Place Operation

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

2:48

Add Two PyTorch Tensors Together

Add two PyTorch Tensors together by using the PyTorch add operation

2:00

Specify PyTorch Tensor Maximum Value Threshold

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

1:59

Specify PyTorch Tensor Minimum Value Threshold

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

2:06

Clip pytorch tensor values to a range 280x158

PyTorch Clamp: Clip PyTorch Tensor Values To A Range

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

1:48

Generate TensorFlow Tensor Full Of Random Numbers In A Given Range

Generate TensorFlow Tensor full of random numbers in a given range by using TensorFlow's random_uniform operation

3:03

Use TensorFlow reshape To Infer Reshaped Tensor's New Dimensions

Use the TensorFlow reshape operation to infer a tensor's new dimensions when reshaping a tensor

6:28

Get The PyTorch Variable Shape

Get the PyTorch Variable shape by using the PyTorch size operation

1:56

Calculate The Biased Standard Deviation Of All Elements In A PyTorch Tensor

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

4:47

Calculate The Unbiased Standard Deviation Of All Elements In A PyTorch Tensor

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

5:00

Calculate The Power Of Each Element In A PyTorch Tensor For A Given Exponent

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

2:04

Calculate The Sum Of All Elements In A PyTorch Tensor

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

2:00

Calculate The Mean Value Of All Elements In A PyTorch Tensor

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

2:01

Use TensorFlow reshape To Change The Shape Of A Tensor

Use TensorFlow reshape to change the shape of a TensorFlow Tensor as long as the number of elements stay the same

5:29

Convert CIFAR10 Dataset from PIL Images to PyTorch Tensors

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

1:15

Check For Element Wise Equality Between Two PyTorch Tensors

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

3:00

Multiply two matricies using tensorflow matmul 280x158

tf.matmul: Multiply Two Matricies Using TensorFlow MatMul

tf.matmul - Multiply two matricies by using TensorFlow's matmul operation

3:35

Create A PyTorch Tensor Full Of Ones

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

1:17

Create A PyTorch Tensor Full Of Zeros

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

1:20

Examine MNIST Dataset from PyTorch Torchvision

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

2:57

Load mnist dataset from pytorch torchvision 280x158

PyTorch MNIST: Load MNIST Dataset from PyTorch Torchvision

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

2:11

Calculate the element wise hadamard multiplication of two tensorflow tensors 280x158

TensorFlow Element Wise Multiplication

TensorFlow Element Wise Multiply of Tensors to get the Hadamard product

4:10

Stack a list of tensorflow tensors into one tensor 280x158

tf.stack: How To Use TensorFlow Stack Operation

tf.stack - How to use tf stack operation to stack a list of TensorFlow tensors

4:58

Load cifar10 dataset from pytorch torchvision 280x158

CIFAR10 PyTorch: Load CIFAR10 Dataset from Torchvision

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

1:59

Check for element wise equality between two tensorflow tensors 280x158

TensorFlow Equal: Compare Two Tensors Element Wise

TensorFlow Equal - Compare two tensors element wise for equality

5:08

Create a tensorflow tensor full of ones 280x158

tf.ones: How To Use tf ones Operation

tf.ones - How to use tf ones operation to create a TensorFlow ones Tensor

2:40

Create a tensorflow tensor full of zeros 280x158

tf.zeros: How To Use tf zeros Operation

tf.zeros - How to use tf zeros operation to create a TensorFlow zeros Tensor

2:52

Calculate column sum in tensorflow 280x158

tf.reduce_sum: Sum Along Axis

tf.reduce_sum - Sum Along Axis Using TensorFlow reduce_sum

3:33

Use tensorflow constant initializer to do simple initialization 280x158

tf.constant_initializer: TensorFlow Constant Initializer

tf.constant_initializer - Use TensorFlow constant initializer operation to initialize a constant in TensorFlow

2:58

Initialize a tensorflow variable with numpy values 280x158

tf.variable: TensorFlow Variable Initialize With NumPy Values

tf.variable - TensorFlow variable initialize with NumPy Values by using tf's get_variable operation

3:15

Create a tensorflow constant tensor populated with a scalar value 280x158

tf.constant: Create Tensorflow Constant Tensor

tf.constant - Create Tensorflow constant tensor with scalar value using tf constant operation.

3:16

Sum a list of tensorflow tensors 280x158

TensorFlow Sum: Use tf.add_n To Sum List of Tensors

TensorFlow Sum - Use TensorFlow's add_n (tf.add_n) to sum list of Tensors

3:55

Initialize tensorflow variable as identity matrix 280x158

Initialize TensorFlow Variables With Matrix

Initialize TensorFlow variables with matrix of your choice. Example with identity matrix.

3:11

Create an identity matrix using tensorflow 280x158

TensorFlow Identity Matrix Creation

TensorFlow Identity Matrix Creation with TensorFlow eye (tf.eye)

3:03

tf.placeholder: Create A TensorFlow Placeholder Tensor

tf.placeholder - Create A TensorFlow Placeholder Tensor and then when it needs to be evaluated pass a NumPy multi-dimensional array into the feed_dict so that the values are used within the TensorFlow session

4:39

Transfer a 1 d tensor to a vector using tensorflow 280x158

TensorFlow squeeze: Use tf.squeeze to remove a dimension from Tensor

TensorFlow squeeze - Use tf.squeeze to remove a dimension from Tensor in order to transfer a 1-D Tensor to a Vector

2:48

Calculate the element wise hadamard multiplication of matrices in pytorch 280x158

PyTorch Element Wise Multiplication

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

2:59

Add two tensorflow tensors together 280x158

TensorFlow Add: Add Two TensorFlow Tensors Together

TensorFlow Add - Use TensorFlow's tf.add to add two Tensors together

2:57

get_tensor_by_name: Get A TensorFlow Variable Tensor By Name

get_tensor_by_name - TensorFlow get variable by name by using the TensorFlow get_default_graph operation and then the TensorFlow get_tensor_by_name operation

2:32

Use feed dict to feed values to tensorflow placeholders 280x158

TensorFlow feed_dict: Use feed_dict To Feed Values To TensorFlow Placeholders

TensorFlow feed_dict example: Use feed_dict to feed values to TensorFlow placeholders so that you don't run into the error that says you must feed a value for placeholder tensors

3:35

PyTorch Tensor Shape: Get the PyTorch Tensor size

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

2:12

Print a verbose version of a pytorch tensor 280x158

PyTorch Print Tensor: Print Full Tensor in PyTorch

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

2:27

Calculate mean of a tensor along an axis using tensorflow 280x158

tf.reduce_mean: Calculate Mean of A Tensor Along An Axis Using TensorFlow

tf.reduce_mean - Use TensorFlow reduce_mean operation to calculate the mean of tensor elements along various dimensions of the tensor

4:32

Initialize tensorflow variables that depend on other tensorflow variables 280x158

TensorFlow Initialize Global Variables: Initialize TensorFlow Variables That Depend On Other TensorFlow Variables

TensorFlow Initialize Global Variables - Initialize TensorFlow Variables That Depend On Other TensorFlow Variables by using the TensorFlow initialized_value functionality

5:00

Convert MXNet NDArray to NumPy Multidimensional Array

Convert an MXNet NDArray to a NumPy Multidimensional Array so that it retains the specific data type using the asnumpy MXNet function

2:40

Convert a pytorch variable to numpy array 280x158

PyTorch Variable To NumPy: Convert PyTorch autograd Variable To NumPy Multidimensional Array

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

3:30

Calculate max of a tensor along an axis using tensorflow 280x158

tf.reduce_max: Calculate Max Of A Tensor Along An Axis Using TensorFlow

tf.reduce_max - Calculate the max of a TensorFlow tensor along a certain axis of the tensor using the TensorFlow reduce_max operation

6:24

Visualize Training Results With TensorFlow summary and TensorBoard

Visualize the training results of running a neural net model with TensorFlow summary and TensorBoard

4:09

Calculate max of a tensorflow tensor 280x158

TensorFlow Max: Use tf.reduce_max To Get Max Value Of A TensorFlow Tensor

TensorFlow Max - Use tf.reduce_max to get max value of a TensorFlow Tensor

2:34

Use tensorflow reshape to convert a tensor to a vector 280x158

tf.reshape: Use TensorFlow reshape To Convert A Tensor To A Vector

tf.reshape - Use TensorFlow reshape to convert a tensor to a vector by understanding the two arguments you must pass to the reshape operation and how the special value of negative one flattens the input tensor

4:18

Convert a numpy array to mxnet ndarray 280x158

MXNet NDArray: Convert NumPy Array To MXNet NDArray

MXNet NDArray - Convert A NumPy multidimensional array to an MXNet NDArray so that it retains the specific data type

3:47

Add Layers To A Neural Network In TensorFlow

Add Multiple Layers to a Neural Network in TensorFlow by working through an example where you add multiple ReLU layers and one convolutional layer

4:19

Convert a pytorch tensor to numpy array 280x158

PyTorch Tensor to NumPy: Convert A PyTorch Tensor To A Numpy Multidimensional Array

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

3:57

Print the value of a tensor object in tensorflow 280x158

TensorFlow Print: Print The Value Of A Tensor Object In TensorFlow

TensorFlow Print - Print the value of a tensor object in TensorFlow by understanding the difference between building the computational graph and running the computational graph

3:36

Generate a random tensor in tensorflow 280x158

tf.concat: Concatenate TensorFlow Tensors Along A Given Dimension

tf.concat - Use tf.concat, TensorFlow's concatenation operation, to concatenate TensorFlow tensors along a given dimension

4:55

Save The State Of A TensorFlow Model With Checkpointing

Save The State Of A TensorFlow Model With Checkpointing Using The TensorFlow Saver Variable To Save The Session Into TensorFlow ckpt Files.

3:27

tf.random_uniform: Generate A Random Tensor In Tensorflow

tf.random_uniform - Generate a random tensor in TensorFlow so that you can use it and maintain it for further use even if you call session run multiple times

4:09

Add Metrics Reporting To Improve Your TensorFlow Neural Network Model

Add Metrics Reporting to Improve Your TensorFlow Neural Network Model So You Can Monitor How Accuracy And Other Measures Evolve As You Change Your Model.

4:38

PyTorch Variable: Create A PyTorch Variable

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

1:36

Train a one layer feed forward neural network in tensorflow 280x158

Train A One Layer Feed Forward Neural Network in TensorFlow With ReLU Activation

Train A One Layer Feed Forward Neural Network in TensorFlow With ReLU Activation, Softmax Cross Entropy with Logits, and the Gradient Descent Optimizer

3:00

Convert a numpy array to a pytorch tensor 280x158

PyTorch NumPy to tensor: Convert A NumPy Array To A PyTorch Tensor

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

1:53

Create a one layer feed forward neural network in tensorflow 280x158

Create A One Layer Feed Forward Neural Network In TensorFlow With ReLU Activation

Create a one layer feed forward neural network in TensorFlow with ReLU activation and understand the context of the shapes of the Tensors

2:04

Concatenate pytorch tensors along a given dimension 280x158

PyTorch Concatenate: Concatenate PyTorch Tensors Along A Given Dimension With PyTorch cat

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

4:45

Load the mnist data set in tensorflow 280x158

Load The MNIST Data Set in TensorFlow So That It Is In One Hot Encoded Format

Import the MNIST data set from the Tensorflow Examples Tutorial Data Repository and encode it in one hot encoded format.

2:29

Cast a pytorch tensor to another type 280x158

PyTorch Change Tensor Type: Cast A PyTorch Tensor To Another Type

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

3:06

Print and check pytorch tensor type 280x158

PyTorch Tensor Type: Print And Check PyTorch Tensor Type

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

1:42

Tensor to NumPy: NumPy Array To Tensorflow Tensor And Back

Tensor to NumPy - Convert a NumPy array to a Tensorflow Tensor as well as convert a TensorFlow Tensor to a NumPy array

1:30

torch create tensor: Construct a PyTorch Tensor

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

1:49

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