Skip to content

akyadav26/Backprop

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

18 Commits
 
 
 
 
 
 

Repository files navigation

253_PA2

The final_version.py file has the final code (adapted from the starter: neuralnet.py).

final_version.py can be run from the same directory that contains config.yaml, and it plots the required graphs for the parameters specified by the config file, and reports the test accuracy.

It also prints out numerical approximates of gradients, actual gradient values and their difference for 10 training examples, each of a different category, for the weight specified in the main function's call to gradient function. The weight can be specified in this call by passing the values of the layer, the input and output indices and whether or not it's a bias unit.

About

Python code for implementing Backprop using numpy

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Contributors 3

  •  
  •  
  •