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Evan evdcush

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@icetee
icetee / win10_normalizer.ps1
Last active October 25, 2023 04:41
Windows 10 remove unnecessary applications
#Uninstall 3D Builder
Get-AppxPackage *3dbuilder* | Remove-AppxPackage
#Uninstall Alarms and Clock
Get-AppxPackage *windowsalarms* | Remove-AppxPackage
#Uninstall Calculator
Get-AppxPackage *windowscalculator* | Remove-AppxPackage
#Uninstall Calendar and Mail:
@claymcleod
claymcleod / pycurses.py
Last active April 28, 2025 17:11
Python curses example
import sys,os
import curses
def draw_menu(stdscr):
k = 0
cursor_x = 0
cursor_y = 0
# Clear and refresh the screen for a blank canvas
stdscr.clear()
@danijar
danijar / blog_tensorflow_scope_decorator.py
Last active January 17, 2023 01:58
TensorFlow Scope Decorator
# Working example for my blog post at:
# https://danijar.github.io/structuring-your-tensorflow-models
import functools
import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data
def doublewrap(function):
"""
A decorator decorator, allowing to use the decorator to be used without
@steinwaywhw
steinwaywhw / One Liner to Download the Latest Release from Github Repo.md
Last active June 1, 2025 16:50
One Liner to Download the Latest Release from Github Repo
  • Use curl to get the JSON response for the latest release
  • Use grep to find the line containing file URL
  • Use cut and tr to extract the URL
  • Use wget to download it
curl -s https://api.github.com/repos/jgm/pandoc/releases/latest \
| grep "browser_download_url.*deb" \
| cut -d : -f 2,3 \
| tr -d \" \
@romanlevin
romanlevin / bash_prompt.sh
Last active May 25, 2022 02:35 — forked from insin/bash_prompt.sh
Set color bash prompt according to active pyenv, git branch and return status of last command.
#!/bin/bash
#
# DESCRIPTION:
#
# Set the bash prompt according to:
# * the active virtualenv
# * the branch/status of the current git repository
# * the return value of the previous command
# * the fact you just came from Windows and are used to having newlines in
# your prompts.
@kennwhite
kennwhite / 1944_OSS_Simple_Sabotage_Field_Manual.md
Last active February 11, 2025 11:57
1944 OSS Simple Sabotage Field Manual
@mivade
mivade / cli.py
Last active March 20, 2025 12:56
Using a decorator to simplify subcommand creation with argparse
"""This is free and unencumbered software released into the public domain.
Anyone is free to copy, modify, publish, use, compile, sell, or
distribute this software, either in source code form or as a compiled
binary, for any purpose, commercial or non-commercial, and by any
means.
In jurisdictions that recognize copyright laws, the author or authors
of this software dedicate any and all copyright interest in the
software to the public domain. We make this dedication for the benefit
@lightonphiri
lightonphiri / bash-install_google_fonts_on_ubuntu.md
Last active May 4, 2025 15:20
Install Google Fonts on Ubuntu

Install Google Fonts

Download desired fonts

https://fonts.google.com/?selection.family=Open+Sans

Install Google Fonts on Ubuntu

cd /usr/share/fonts
sudo mkdir googlefonts
cd googlefonts
sudo unzip -d . ~/Downloads/Open_Sans.zip

@anthonyray
anthonyray / gist:398fde676a7704c03d6624155ba0011e
Last active May 6, 2024 06:15
Set up OhMyZsh on Amazon EC2 instance running Ubuntu Server 14.04
  1. Connect to your EC2 instance
  2. Install zsh : sudo apt-get update && sudo apt-get install zsh
  3. Edit your passwd configuration file to tell which shell to use for user ubuntu : sudo vim /etc/passwd
  4. Look for ubuntu user, and replace bin/bash by bin/zsh
  5. Install OhMyZsh : sh -c "$(wget https://raw.githubusercontent.com/robbyrussell/oh-my-zsh/master/tools/install.sh -O -)"
  6. Disconnect from your instance and reconnect it.
@karpathy
karpathy / nes.py
Last active January 15, 2025 02:40
Natural Evolution Strategies (NES) toy example that optimizes a quadratic function
"""
A bare bones examples of optimizing a black-box function (f) using
Natural Evolution Strategies (NES), where the parameter distribution is a
gaussian of fixed standard deviation.
"""
import numpy as np
np.random.seed(0)
# the function we want to optimize