hofmannsven

Git

Global Settings

• Related Setup: https://gist.github.com/hofmannsven/6814278
• Related Pro Tips: https://ochronus.com/git-tips-from-the-trenches/
• Interactive Beginners Tutorial: http://try.github.io/
• Git Cheatsheet by GitHub: https://services.github.com/on-demand/downloads/github-git-cheat-sheet/

Reminder

Press minus + shift + s and return to chop/fold long lines!

chfritz

%% /** ---------------------------------------------------------
%%      a file full of squeezing options 
%%      -- which you should try to avoid
%% -------------------------------------------------------------
%%
%% from:
%% http://www.eng.cam.ac.uk/help/tpl/textprocessing/squeeze.html    
%% ---------------------------------------------------------- */
%%     * Page Layout
%%           o \columnsep: gap between columns

mjohnsullivan

import os.path
import shutil
import hashlib
import logging

# Support both Python 2 and 3 urllib2 importing
try:
    from urllib.request import urlopen, Request
except ImportError:
    from urllib2 import urlopen, Request

fperez

ctokheim

Cython

Cython has two major benefits:

1. Making python code faster, particularly things that can't be done in scipy/numpy
2. Wrapping/interfacing with C/C++ code

Cython gains most of it's benefit from statically typing arguments. However, statically typing is not required, in fact, regular python code is valid cython (but don't expect much of a speed up). By incrementally adding more type information, the code can speed up by several factors. This gist just provides a very basic usage of cython.

debasishg

1. Feature Learning

• Learning Feature Representations with K-means by Adam Coates and Andrew Y. Ng
• The devil is in the details: an evaluation of recent feature encoding methods by Chatfield et. al.
• Emergence of Object-Selective Features in Unsupervised Feature Learning by Coates, Ng
• Scaling Learning Algorithms towards AI Benjio & LeCun
• A Theory of Feature Learning by Brendan van Rooyen, Robert C. Williamson

2. Deep Learning

• Dropout: A Simple Way to Prevent Neural Networks from Overfitting by Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever and Ruslan Salakhutdinov
• [Understanding

kastnerkyle

# Alec Radford, Indico, Kyle Kastner
# License: MIT
"""
Convolutional VAE in a single file.
Bringing in code from IndicoDataSolutions and Alec Radford (NewMu)
Additionally converted to use default conv2d interface instead of explicit cuDNN
"""
import theano
import theano.tensor as T
from theano.compat.python2x import OrderedDict

iamtekeste

Download Google Drive files with WGET

Example Google Drive download link:

https://docs.google.com/open?id=[ID]
To download the file with WGET you need to use this link:

https://googledrive.com/host/[ID]

Example WGET command:

patik

Squashing Git Commits

The easy and flexible way

This method avoids merge conflicts if you have periodically pulled master into your branch. It also gives you the opportunity to squash into more than 1 commit, or to re-arrange your code into completely different commits (e.g. if you ended up working on three different features but the commits were not consecutive).

Note: You cannot use this method if you intend to open a pull request to merge your feature branch. This method requires committing directly to master.

Switch to the master branch and make sure you are up to date:

karpathy

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)