alexjc

Specific Papers

• https://arxiv.org/abs/1505.07376

  Texture Synthesis Using Convolutional Neural Networks
• https://arxiv.org/abs/1508.06576

  A Neural Algorithm of Artistic Style
• https://arxiv.org/abs/1603.03417

  Texture Networks: Feed-forward Synthesis of Textures and Stylized Images
• https://arxiv.org/abs/1701.02096

  Improved Texture Networks: Maximizing Quality and Diversity in Feed-forward Texture Synthesis

joepie91

Don't use VPN services.

No, seriously, don't. You're probably reading this because you've asked what VPN service to use, and this is the answer.

Note: The content in this post does not apply to using VPN for their intended purpose; that is, as a virtual private (internal) network. It only applies to using it as a glorified proxy, which is what every third-party "VPN provider" does.

• A Russian translation of this article can be found here, contributed by Timur Demin.
• A Turkish translation can be found here, contributed by agyild.
• There's also this article about VPN services, which is honestly better written (and has more cat pictures!) than my article.

paulirish

/* bling.js */
window.$ = document.querySelector.bind(document);
window.$$ = document.querySelectorAll.bind(document);
Node.prototype.on = window.on = function(name, fn) { this.addEventListener(name, fn); };
NodeList.prototype.__proto__ = Array.prototype;
NodeList.prototype.on = function(name, fn) { this.forEach((elem) => elem.on(name, fn)); };

isaacs

# Hello, and welcome to makefile basics.
#
# You will learn why `make` is so great, and why, despite its "weird" syntax,
# it is actually a highly expressive, efficient, and powerful way to build
# programs.
#
# Once you're done here, go to
# http://www.gnu.org/software/make/manual/make.html
# to learn SOOOO much more.

stormpython

Data Visualization with Elasticsearch Aggregations and D3

Link to the Elasticsearch Blog.

fyears

if you are using linux, unix, os x:

pip install -U setuptools
pip install -U pip

pip install numpy
pip install scipy
pip install matplotlib
#pip install PySide

mdml

A dendrogram is a common way to represent hierarchical data. For Python users, Scipy has a hierarchical clustering module that performs hierarchical clustering and outputs the results as dendrogram plots via matplotlib. When it's time to make a prettier, more customized, or web-version of the dendogram, however, it can be tricky to use Scipy's dendrogram to create a suitable visualization. My preferred method of visualizing data -- especially on the web -- is D3. This example includes a script to convert a Scipy dendrogram into JSON format used by D3's cluster method.

In the example, I cluster six genes by their expression values from two experiments. You can easily replace that data with your own, larger data set, to harness the power of both Scipy and D3 for analyzing hierarchical data. The D3 code I used to generate this example is straigh

goldsmith

# A guide to prevent pain and suffering while upgrading to OS X Mavericks
# This will vary greatly depending on system set up, so read the instructions carefully

# Back up Virtulenvs
####################

# Very important! 
# For each virtualenv you have, run "pip freeze > requirements.txt" while in the activated virtualenv 
# in order to prevent loss of dependencies during the upgrade.

millermedeiros

Setup Mac OS X

I've done the same process every couple years since 2013 (Mountain Lion, Mavericks, High Sierra, Catalina) and I updated the Gist each time I've done it.

I kinda regret for not using something like Boxen (or anything similar) to automate the process, but TBH I only actually needed to these steps once every couple years...

svonava

import re
from datetime import timedelta
regex = re.compile(r'((?P<hours>\d+?)h)? ((?P<minutes>\d+?)m)? ((?P<seconds>\d+?)s)?')
regex2 = re.compile(r'((?P<minutes>\d+?)m)? ((?P<seconds>\d+?)s)?')
def parse_time(time_str):
    parts = regex.match(time_str)
    if not parts:
        parts = regex2.match(time_str)
    parts = parts.groupdict()
    time_params = {}