Data

Tools

Indexes

Applications

Experiments

Open Source Science

https://github.com/fgnt/2019_ad_xidian

https://github.com/fgnt/2019_ad_xidian

Science Score: 8.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ○
    codemeta.json file
  • ○
    .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ○
    Academic email domains
  • ✓
    Institutional organization owner
    Organization fgnt has institutional domain (nt.uni-paderborn.de)
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (6.5%) to scientific vocabulary
Last synced: 9 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: fgnt
  • Language: HTML
  • Default Branch: master
  • Size: 227 KB
Statistics
  • Stars: 0
  • Watchers: 4
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created almost 7 years ago · Last pushed almost 7 years ago

https://github.com/fgnt/2019_ad_xidian/blob/master/ 

# Introduction
 https://fgnt.github.io/2019_ad_xidian/ 

# Theoretical exercise
 https://github.com/fgnt/2019_ad_xidian/blob/master/theory/exercise.pdf

# Practical exercise
Start a jupyter notebook server in the poolroom:
```bash
source /upb/scratch/users/c/cbj/py37/bin/activate
cd ~/ && jupyter notebook
```
For more details see:
https://fgnt.github.io/python_crashkurs_doc/include/poolroom.html

Small numpy introduction: https://fgnt.github.io/python_crashkurs_doc/include/numpy.html
Numpy cheat sheet: https://git.cs.upb.de/chthiel/python-tutorial/blob/master/cheat_sheets/Numpy_Python_Cheat_Sheet.pdf



## Download the exercise:
Download the git repository
```bash
git clone https://github.com/fgnt/2019_ad_xidian.git
```
Now you can find in your home directory a notebook to start the exercise
(`~/2019_ad_xidian/practice/ad_template.ipynb`) and a python script that contains some helper functions (`~/2019_ad_xidian/practice/ad_helper.py`).

Alternative:
Open 
https://raw.githubusercontent.com/fgnt/2019_ad_xidian/master/practice/ad_template.ipynb
in a browser and safe the file.

# Final task

Extend the code in jupyter notebook from the practical exercise to a full neuronal network (NN) framework
and train a NN on the MNIST data.
Can you reach 98% accuracy?

Owner

  • Name: Department of Communications Engineering University of Paderborn
  • Login: fgnt
  • Kind: organization
  • Location: Paderborn, Germany

GitHub Events

Total
Last Year