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Achilles Rasquinha achillesrasquinha

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View frappe-bench-frappe-default-worker.service
ExecStart=/home/revant/.local/bin/bench worker --queue default
jorgebucaran / index.html
Last active July 14, 2020 06:37
Getting started with Hyperapp
View index.html
<!DOCTYPE html>
<html lang="en">
<script type="module">
import { h, text, app } from ""
init: () => 0,
view: state =>
h("main", {}, [
RDCH106 /
Created October 5, 2016 10:06
ANSI Colors Fix for Python in Windows
import os
import platform
if == 'nt' and platform.release() == '10' and platform.version() >= '10.0.14393':
# Fix ANSI color in Windows 10 version 10.0.14393 (Windows Anniversary Update)
import ctypes
kernel32 = ctypes.windll.kernel32
kernel32.SetConsoleMode(kernel32.GetStdHandle(-11), 7)
PieterScheffers / start_docker_registry.bash
Last active December 29, 2022 10:25
Start docker registry with letsencrypt certificates (Linux Ubuntu)
View start_docker_registry.bash
#!/usr/bin/env bash
# install docker
# install docker-compose
# install letsencrypt
graceavery / harryPotterAliases
Last active August 22, 2021 14:17
bash aliases for Harry Potter enthusiasts
View harryPotterAliases
alias accio=wget
alias avadaKedavra='rm -f'
alias imperio=sudo
alias priorIncantato='echo `history |tail -n2 |head -n1` | sed "s/[0-9]* //"'
alias stupefy='sleep 5'
alias wingardiumLeviosa=mv
alias sonorus='set -v'
alias quietus='set +v'
klmr / Makefile
Last active January 27, 2023 14:12
Self-documenting makefiles
View Makefile
# Example makefile with some dummy rules
.PHONY: all
## Make ALL the things; this includes: building the target, testing it, and
## deploying to server.
all: test deploy
.PHONY: build
# No documentation; target will be omitted from help display
learncodeacademy / webpack.config.js
Created January 8, 2016 03:55
Sample Basic Webpack Config
View webpack.config.js
var debug = process.env.NODE_ENV !== "production";
var webpack = require('webpack');
module.exports = {
context: __dirname,
devtool: debug ? "inline-sourcemap" : null,
entry: "./js/scripts.js",
output: {
path: __dirname + "/js",
filename: "scripts.min.js"
vinhkhuc /
Last active December 22, 2021 11:52
Simple Feedforward Neural Network using TensorFlow
# Implementation of a simple MLP network with one hidden layer. Tested on the iris data set.
# Requires: numpy, sklearn>=0.18.1, tensorflow>=1.0
# NOTE: In order to make the code simple, we rewrite x * W_1 + b_1 = x' * W_1'
# where x' = [x | 1] and W_1' is the matrix W_1 appended with a new row with elements b_1's.
# Similarly, for h * W_2 + b_2
import tensorflow as tf
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
wangruohui / Caffe Ubuntu
Last active November 8, 2021 18:36
Compile and run Caffe on Ubuntu 15.10
View Caffe Ubuntu

Ubuntu 15.10 have been released for a couple of days. It is a bleeding-edge system coming with Linux kernel 4.2 and GCC 5. However, compiling and running Caffe on this new system is no longer as smooth as on earlier versions. I have done some research related to this issue and finally find a way out. I summarize it here in this short tutorial and I hope more people and enjoy this new system without breaking their works.

Install NVIDIA Driver

The latest NVIDIA driver is officially included in Ubuntu 15.10 repositories. One can install it directly via apt-get.

sudo apt-get install nvidia-352-updates nvidia-modprobe

The nvidia-modprobe utility is used to load NVIDIA kernel modules and create NVIDIA character device files automatically everytime your machine boots up.

Reboot your machine and verify everything works by issuing nvidia-smi or running deviceQuery in CUDA samples.

dennybritz /
Created September 18, 2015 16:45
# Helper function to plot a decision boundary.
# If you don't fully understand this function don't worry, it just generates the contour plot below.
def plot_decision_boundary(pred_func):
# Set min and max values and give it some padding
x_min, x_max = X[:, 0].min() - .5, X[:, 0].max() + .5
y_min, y_max = X[:, 1].min() - .5, X[:, 1].max() + .5
h = 0.01
# Generate a grid of points with distance h between them
xx, yy = np.meshgrid(np.arange(x_min, x_max, h), np.arange(y_min, y_max, h))
# Predict the function value for the whole gid