Some basic usage:
- Constants, Variables, Placeholders
- Example on Model Building and Training
- Example on Saving and Restoring Saved Models/Variables
- Tracking accuracy and loss function during training and visualizing them using TensorBoard
More resources and examples (on MNIST), if you are still struggling:
- Logistic Regression sample code
- NN sample code
- Saving and loading/restoring a model sample code
- Saving summary variables to visualize in TensorBoard sample code
Note: These are a bit old, so there might have bit some changes in syntax in more recent version of TF. Let us know, if you have any trouble with them.
tensorflow
numpy
tensorboard
Also a working installation of ipython/jupyter.
Clone/Fork repository:
>> git clone https://github.com/compgi13/tutorial.git
Go to the folder and start a session:
>> cd tutorial
>> ipython notebook
Select the notebook you want and run through the tutorial.