Sebastian Gutierrez
Browse Sebastian Gutierrez's Lessons
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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 Nonestyle 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 Nonestyle 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 Nonestyle indexing
1:37

Calculate The Number Of Elements In A PyTorch Tensor
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




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 inplace 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
Clip PyTorch Tensor values to a range by using the PyTorch clamp operation
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 Matrices Using TensorFlow MatMul
Multiply two matricies by using TensorFlow's matmul operation
3:35

Calculate The ElementWise Hadamard Multiplication Of Two TensorFlow Tensors
Calculate the elementwise Hadamard multiplication of two TensorFlow tensors by using tf.multiply
4:10

Stack A List of TensorFlow Tensors Into One Tensor
Stack a list of TensorFlow Tensors of the same rank into one tensor by using tf.stack
4:58

Check For Element Wise Equality Between Two TensorFlow Tensors
Check for element wise equality between two TensorFlow Tensors by using the TensorFlow equal operator to do the comparison.
5:08

Create A TensorFlow Tensor Full of Ones
Create a TensorFlow Constant Tensor full of ones so that each element is a one using the TensorFlow Ones operation.
2:40

Create A TensorFlow Tensor Full of Zeros
Create a TensorFlow Constant Tensor full of zeros so that each element is a zero using the TensorFlow Zeros operation.
2:52

Calculate Column Sum In TensorFlow
Do a column sum in TensorFlow using tf.reduce_sum to get the sum of all of the elements in the columns of a Tensor
3:33

Use TensorFlow Constant Initializer To Do Simple Initialization
Use the TensorFlow constant_initializer operation to do a simple TensorFlow Variable creation such that the initialized values of the variable get the value that you pass into it.
2:58

Initialize A TensorFlow Variable With NumPy Values
Initialize a TensorFlow Variable with NumPy values by using TensorFlow's get_variable operation and setting the Variable initializer to the NumPy values
3:15

Create A TensorFlow Constant Tensor Populated With A Scalar Value
Create a TensorFlow Constant Tensor populated with a scalar value by using the TensorFlow Constant operation as well as defining the shape and data type
3:16

Sum A List Of TensorFlow Tensors
Sum a list of TensorFlow Tensors using the TensorFlow add_n operation so that you can add more than two TensorFlow Tensors together at the same time
3:55

Initialize TensorFlow Variable As Identity Matrix
Initialize a TensorFlow Variable as the identity matrix of the shape of your choosing using the TensorFlow Variable Functionality and the Tensorflow Eye Functionality
3:11

Create An Identity Matrix Using TensorFlow
Create An Identity Matrix Using The TensorFlow Eye Functionality
3:03

Create A TensorFlow Placeholder Tensor
Create A TensorFlow Placeholder Tensor and then when it needs to be evaluated pass a NumPy multidimensional array into the feed_dict so that the values are used within the TensorFlow session
4:39

Transfer A 1D Tensor To A Vector Using TensorFlow
Transfer a 1D Tensor to a Vector using the TensorFlow squeeze transformation to remove the dimension of size 1 from the shape of the tensor
2:48

Calculate The ElementWise Hadamard Multiplication Of Matrices In PyTorch
Calculate the ElementWise multiplication of matrices in PyTorch to get the Hadamard Product
2:59

Add Two TensorFlow Tensors Together
Add two TensorFlow Tensors together by using the TensorFlow add operation
2:57

Get A TensorFlow Tensor By Name
Get A TensorFlow Tensor 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
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

Get The PyTorch Tensor Shape
Get the PyTorch Tensor shape as a PyTorch Size object and as a list of integers
2:12

Print A Verbose Version Of A PyTorch Tensor
Print a verbose version of a PyTorch tensor 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
Use TensorFlow reduce_mean operation (tf.reduce_mean) to calculate the mean of tensor elements along various dimensions of the tensor
4:32

Initialize TensorFlow Variables That Depend On Other TensorFlow 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 PyTorch autograd Variable To NumPy Multidimensional Array
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
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
Calculate the max of a TensorFlow tensor using the TensorFlow reduce_max operation
2:34

Use TensorFlow reshape To Convert A Tensor To A Vector
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 NumPy Array To 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 A Numpy Multidimensional Array
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
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

Concatenate TensorFlow Tensors Along A Given Dimension
Concatenate TensorFlow tensors along a given dimension using the TensorFlow concatenation concat functionality and then check the shape of the concatenated tensor using the TensorFlow shape functionality
4:55

Generate A Random Tensor In Tensorflow
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

Create A 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
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
Concatenate A List of PyTorch Tensors Along A Given Dimension
4:45


Print And Check PyTorch Tensor Type
Print out the PyTorch Tensor type without printing out the whole PyTorch Tensor.
1:42

Construct a PyTorch Tensor
Create an uninitialized PyTorch Tensor and an initialized PyTorch Tensor.
1:49