pachadotdev

# Option 1: Use apt-get

# keys taken from https://software.intel.com/en-us/articles/installing-intel-free-libs-and-python-apt-repo
cd ~/GitHub/r-with-intel-mkl/
wget https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS-2019.PUB
apt-key add GPG-PUB-KEY-INTEL-SW-PRODUCTS-2019.PUB

sudo sh -c 'echo deb https://apt.repos.intel.com/mkl all main > /etc/apt/sources.list.d/intel-mkl.list'
sudo apt-get update && sudo apt-get install intel-mkl-64bit

cmizony

"    _____ __  __ _____ __________  _   ___     __                 _
"   / ____|  \/  |_   _|___  / __ \| \ | \ \   / /                (_)
"  | |    | \  / | | |    / / |  | |  \| |\ \_/ /   ______  __   ___ _ __ ___  _ __ ___
"  | |    | |\/| | | |   / /| |  | | . ` | \   /   |______| \ \ / / | '_ ` _ \| '__/ __|
"  | |____| |  | |_| |_ / /_| |__| | |\  |  | |              \ V /| | | | | | | | | (__
"   \_____|_|  |_|_____/_____\____/|_| \_|  |_|               \_/ |_|_| |_| |_|_|  \___|
"
"
" 1. Easy navigation in .vimrc:
"   Use <Leader>ig to view indentation guides

sloria

The Best of the Best Practices (BOBP) Guide for Python

A "Best of the Best Practices" (BOBP) guide to developing in Python.

In General

Values

• "Build tools for others that you want to be built for you." - Kenneth Reitz
• "Simplicity is alway better than functionality." - Pieter Hintjens

MohamedAlaa

tmux shortcuts & cheatsheet

start new:

tmux

start new with session name:

tmux new -s myname

jboner

Latency Comparison Numbers (~2012)
----------------------------------
L1 cache reference                           0.5 ns
Branch mispredict                            5   ns
L2 cache reference                           7   ns                      14x L1 cache
Mutex lock/unlock                           25   ns
Main memory reference                      100   ns                      20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy             3,000   ns        3 us
Send 1K bytes over 1 Gbps network       10,000   ns       10 us
Read 4K randomly from SSD*             150,000   ns      150 us          ~1GB/sec SSD

entaroadun

Movies Recommendation:

• MovieLens - Movie Recommendation Data Sets http://www.grouplens.org/node/73
• Yahoo! - Movie, Music, and Images Ratings Data Sets http://webscope.sandbox.yahoo.com/catalog.php?datatype=r
• Jester - Movie Ratings Data Sets (Collaborative Filtering Dataset) http://www.ieor.berkeley.edu/~goldberg/jester-data/
• Cornell University - Movie-review data for use in sentiment-analysis experiments http://www.cs.cornell.edu/people/pabo/movie-review-data/

Music Recommendation:

• Last.fm - Music Recommendation Data Sets http://www.dtic.upf.edu/~ocelma/MusicRecommendationDataset/index.html

bradmontgomery

# Install rvm system-wide
bash -s stable < <(curl -s https://raw.github.com/wayneeseguin/rvm/master/binscripts/rvm-installer )

# Update the packages
apt-get update
apt-get upgrade
apt-get install build-essential

# get the packages required by ruby
rvm pkg install zlib

ewheeler

# create stub, then run flask app in tornado on port 5000 (perhaps with supervisord config below http://supervisord.org/index.html)

#!/usr/bin/env python

from tornado.wsgi import WSGIContainer
from tornado.httpserver import HTTPServer
from tornado.ioloop import IOLoop
from myflaskapp import app

http_server = HTTPServer(WSGIContainer(app))