# TensorFlow Tutorial Screencast Videos ## Watch these 51 TensorFlow deep learning tutorials

• ### Calculate TensorFlow Median Value

tf.contrib.distributions.percentile - Calculate TensorFlow Median Value using the percentile distribution and the interpolation methods

1:32

• ### 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

• ### 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.reduce_sum: Sum Along Axis

tf.reduce_sum - Sum Along Axis Using TensorFlow reduce_sum

3:33

• ### 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

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

• ### 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