Skip to content

Latest commit

 

History

History
35 lines (28 loc) · 702 Bytes

File metadata and controls

35 lines (28 loc) · 702 Bytes

ffnn_implementation

Build for course assignment at university of Freiburg: GitHub Page

Installation

  1. Clone repository
  2. install requirements (! use python 2.7)
pip install -r requirements.txt

Run on MNIST dataset

  1. Open python editor (e.x. jupyter notebook)
  2. Import run_mnist.py
  3. Train neural network
  4. Compute test error and show images that are classified right and wrong
import run_mnist as r
nn = r.train_mnist(0.7,100,100)
r.test_mnist(nn)

Check gradients of neural network

  1. Open python editor (e.x. jupyter notebook)
  2. Import run_gradient_checking.py
import run_gradient_checking