Sebastian Gutierrez is an AI Workbox Instructor That Teaches Modern Deep Learning Tools on @aiworkbox

Make A Simple PyTorch Autograd Computational Graph

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

3:49

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

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

tf.transpose: Transpose A Matrix in TensorFlow

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

2:23

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

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

Launch TensorFlow TensorBoard

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

1:23

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

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

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

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

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

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

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

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

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

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

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

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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