TensorFlow Tutorial Screencast Videos
Watch these 50 TensorFlow deep learning tutorials

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

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

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

Convert List To TensorFlow Tensor
Convert a python list into a TensorFlow Tensor using the TensorFlow convert_to_tensor functionality
2:21

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

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

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

tf.matmul: Multiply Two Matricies Using TensorFlow MatMul
tf.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

tf.stack: Stack A List of TensorFlow Tensors Into One Tensor
tf.stack  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

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

tf.zeros: Create A TensorFlow Tensor Full of Zeros
tf.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

tf.add_n: Sum A List Of TensorFlow Tensors
Use TensorFlow's tf.add_n operation to sum a list of tensors 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

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 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

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

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

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

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

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

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

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

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

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

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

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