Skip to content

Sample code for "Tensorflow and deep learning, without a PhD" presentation and code lab.

License

Notifications You must be signed in to change notification settings

SamilCan/tensorflow-mnist-tutorial

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Image

This is support code for the codelab "Tensorflow and deep learning - without a PhD"

The presentation explaining the underlying concepts is here and you will find codelab instructions to follow on its last slide. Do not forget to open the speaker notes in the presentation, a lot of the explanations are there.

The lab takes 2.5 hours and takes you through the design and optimisation of a neural network for recognising handwritten digits, from the simplest possible solution all the way to a recognition accuracy above 99%. It covers dense and convolutional networks, as well as techniques such as learning rate decay and dropout.

Installation instructions here. The short version is: install Python3, then pip3 install tensorflow and matplotlib.


Disclaimer: This is not an official Google product but sample code provided for an educational purpose

About

Sample code for "Tensorflow and deep learning, without a PhD" presentation and code lab.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 100.0%