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TensorFlow Tutorial Screencast Videos
Watch these 51 TensorFlow deep learning tutorials
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Calculate TensorFlow Median Value
tf.contrib.distributions.percentile - Calculate TensorFlow Median Value using the percentile distribution and the interpolation methods
1:32
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tf.transpose: Transpose A Matrix in TensorFlow
tf.transpose - Use TensorFlow's transpose operation to transpose a TensorFlow matrix tensor
2:23
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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
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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
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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
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Flatten A TensorFlow Tensor
Use the TensorFlow reshape operation to flatten a TensorFlow Tensor
3:17
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Print TensorFlow Tensor Shape
Use the TensorFlow get_shape operation to print the static shape of a TensorFlow tensor as a list
2:35
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Print TensorFlow Version
Find out which version of TensorFlow is installed in your system by printing the TensorFlow version
1:16
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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
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Convert List To TensorFlow Tensor
Convert a python list into a TensorFlow Tensor using the TensorFlow convert_to_tensor functionality
2:21
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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
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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
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Launch TensorFlow TensorBoard
Use the TensorBoard command line utility to launch the TensorFlow TensorBoard web service
1:23
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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
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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
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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
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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
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tf.matmul: Multiply Two Matricies Using TensorFlow MatMul
tf.matmul - Multiply two matricies by using TensorFlow's matmul operation
3:35
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Calculate The Element-Wise Hadamard Multiplication Of Two TensorFlow Tensors
Calculate the element-wise Hadamard multiplication of two TensorFlow tensors by using tf.multiply
4:10
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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
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TensorFlow Equal: Compare Two Tensors Element Wise
TensorFlow Equal - Compare two tensors element wise for equality
5:08
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tf.ones: How To Use tf ones Operation
tf.ones - How to use tf ones operation to create a TensorFlow ones Tensor
2:40
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tf.zeros: How To Use tf zeros Operation
tf.zeros - How to use tf zeros operation to create a TensorFlow zeros Tensor
2:52
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tf.constant_initializer: TensorFlow Constant Initializer
tf.constant_initializer - Use TensorFlow constant initializer operation to initialize a constant in TensorFlow
2:58
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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
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tf.constant: Create Tensorflow Constant Tensor
tf.constant - Create Tensorflow constant tensor with scalar value using tf constant operation.
3:16
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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
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Initialize TensorFlow Variables With Matrix
Initialize TensorFlow variables with matrix of your choice. Example with identity matrix.
3:11
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TensorFlow Identity Matrix Creation
TensorFlow Identity Matrix Creation with TensorFlow eye (tf.eye)
3:03
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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
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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
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TensorFlow Add: Add Two TensorFlow Tensors Together
TensorFlow Add - Use TensorFlow's tf.add to add two Tensors together
2:57
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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