Hi:
perl -e 'print "hello world!\n"'
A simple filter:
perl -ne 'print if /REGEX/'
Filter out blank lines (in place):
========================================== ========================================== | |
TMUX COMMAND WINDOW (TAB) | |
========================================== ========================================== | |
List tmux ls List ^b w | |
New new -s <session> Create ^b c | |
Attach att -t <session> Rename ^b , <name> | |
Rename rename-session -t <old> <new> Last ^b l (lower-L) | |
Kill kill-session -t <session> Close ^b & |
# Step 1: Set priveleges | |
$ sudo /System/Library/CoreServices/RemoteManagement/ARDAgent.app/Contents/Resources/kickstart -configure -allowAccessFor -allUsers -privs -all | |
Starting... | |
Setting allow all users to YES. | |
Setting all users privileges to 1073742079. | |
Done. | |
# Step 2: Allow VNC clients |
license: gpl-3.0 |
Hi:
perl -e 'print "hello world!\n"'
A simple filter:
perl -ne 'print if /REGEX/'
Filter out blank lines (in place):
# coding: utf-8 | |
# Based on https://gist.github.com/netmute/7374150 | |
require 'date' | |
# Run some AppleScript to fetch open tabs from Chrome | |
input = %x{osascript -e 'tell application \"Google Chrome\"' -e 'set tabList to every tab of window 1' -e 'set urlList to \"\"' -e 'repeat with aTab in tabList' -e 'set aLink to URL of aTab' -e 'set aTitle to Title of aTab' -e 'set urlList to urlList & aLink & \"$\" & aTitle & ASCII character 10' -e 'end repeat' -e 'return urlList' -e 'end tell' 2> /dev/null }.chomp | |
A personal diary of DataFrame munging over the years.
Convert Series datatype to numeric (will error if column has non-numeric values)
(h/t @makmanalp)
#!/usr/bin/python | |
# | |
# This script fetches the current open tabs in all Safari windows. | |
# Useful to run remotely on your mac when you are at work and want | |
# to read a page you have open (remotely) at home but don't remember | |
# the url but can log in to your home system on the cmmand line | |
# | |
import sys |
""" | |
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) |
##VGG16 model for Keras
This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.
It has been obtained by directly converting the Caffe model provived by the authors.
Details about the network architecture can be found in the following arXiv paper:
Very Deep Convolutional Networks for Large-Scale Image Recognition
K. Simonyan, A. Zisserman
/* Developed by Daniel Park (github.com/sudocode). | |
* | |
* Free for personal or commercial use, with or without modification. | |
* No warranty is expressed or implied. | |
*/ | |
var App = Application.currentApplication(), | |
Evernote = Application('Evernote'), | |
Notes = Application('Notes') | |