Jaan Altosaar Li jaanli

How to get a free StartSSL.com SSL certificate

I'm writing this up from memory, so errors may appear.

This has been updated to use SHA256 certificates.

Start

Go to http://www.startssl.com/
Click on 'Control Panel'

Default

Powerlevel10k

This is a plain-text version of Bret Victor’s reading list. It was requested by hf on Hacker News.

Highly recommended things!

This is my five-star list. These are my favorite things in all the world.

A few of these works have had an extraordinary effect on my life or way of thinking. They get a sixth star. ★

ImageMagick Video to GIF Optimization Summary

Source

A software developer who uses IM to create Movie GIFs, Benoit Rouleau, in discussion with me, gave me a AVI video of a plane flying over, to help us mutually explore IM video conversion techniques.

Markdown License badges

Collection of License badges for your Project's README file.
This list includes the most common open source and open data licenses.
Easily copy and paste the code under the badges into your Markdown files.

Notes

The badges do not fully replace the license informations for your projects, they are only emblems for the README, that the user can see the License at first glance.

Translations: (No guarantee that the translations are up-to-date)

🇫🇷 Cette liste en français

	It is a rite of passage to post one's successful build instructions for OpenCV on a Mac
	after you've tried all the other conflicting instructions out there and still failed.
	brew failed for me (was this because I could never get a happy brew doctor situation?
	I'll never know). macports? nope. build-from-source recipes? I didn't find one that
	worked for me.

	Here's what did work to build OpenCV 2.4.5 from the distribution tarball using cmake,
	on Mac OSX 10.8.4, linked to an anaconda installation rather than the system python.
	It is a mashup of various bits of advice out there. If you're already comfortable with
	build/install from source, all you need to read is the cmake invocation in step 3 and

	# set up flags for Numpy C extentions compiling
	export CFLAGS="-arch i386 -arch x86_64"
	export FFLAGS="-m32 -m64"
	export LDFLAGS="-Wall -undefined dynamic_lookup -bundle -arch i386 -arch x86_64"
	export CC=gcc-4.2
	export CXX="g++ -arch i386 -arch x86_64"

	pip install numpy
	# success!

	""" Example using GenSim's LDA and sklearn. """

	import numpy as np

	from gensim import matutils
	from gensim.models.ldamodel import LdaModel
	from sklearn import linear_model
	from sklearn.datasets import fetch_20newsgroups
	from sklearn.feature_extraction.text import CountVectorizer

	# Two very basic functions for searching just the input code of an IPython notebook
	# Written because I often want to search notebooks for snippets but the giant output
	# of embedded encoded images makes it difficult.

	# Ipython's nbconvert can be used to extract just the input, but this requires
	# writing to a separate file and can be quite slow when used with large notebooks.
	# Additionally, find/xargs can be used with igrep when the name of the notebook isn't known.

	# icat could be used to convert an IPython notebook to a standard python file if
	# the notebook does not contain whole-cell magics.