Sebastian Gutierrez

Browse Sebastian Gutierrez's Lessons
showing 93 lessons...
-
Make A Simple PyTorch Autograd Computational Graph
Build an autograd backward graph by performing operations on PyTorch Autograd Tensors
3:49
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
-
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
-
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
-
-
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
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
-
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
-
tf.matmul: Multiply Two Matricies Using TensorFlow MatMul
tf.matmul - Multiply two matricies by using TensorFlow's matmul operation
3:35
-
TensorFlow Element Wise Multiplication
TensorFlow Element Wise Multiply of Tensors to get the Hadamard product
4:10
-
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
-
TensorFlow Equal: Compare Two Tensors Element Wise
TensorFlow Equal - Compare two tensors element wise for equality
5:08
-
tf.ones: How To Use tf ones Operation
tf.ones - How to use tf ones operation to create a TensorFlow ones Tensor
2:40
-
tf.zeros: How To Use tf zeros Operation
tf.zeros - How to use tf zeros operation to create a TensorFlow zeros Tensor
2:52
-
-
tf.constant_initializer: TensorFlow Constant Initializer
tf.constant_initializer - Use TensorFlow constant initializer operation to initialize a constant in TensorFlow
2:58
-
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
-
tf.constant: Create Tensorflow Constant Tensor
tf.constant - Create Tensorflow constant tensor with scalar value using tf constant operation.
3:16
-
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 Variables With Matrix
Initialize TensorFlow variables with matrix of your choice. Example with identity matrix.
3:11
-
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
-
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
-
PyTorch Element Wise Multiplication
PyTorch Element Wise Multiplication - Calculate the element wise multiplication to get the Hadamard Product
2:59
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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