A very basic regex-based Markdown parser. Supports the
following elements (and can be extended via Slimdown::add_rule()
):
- Headers
- Links
- Bold
A very basic regex-based Markdown parser. Supports the
following elements (and can be extended via Slimdown::add_rule()
):
Copyright (c) 2013 Ross Kirsling | |
Permission is hereby granted, free of charge, to any person obtaining | |
a copy of this software and associated documentation files (the | |
"Software"), to deal in the Software without restriction, including | |
without limitation the rights to use, copy, modify, merge, publish, | |
distribute, sublicense, and/or sell copies of the Software, and to | |
permit persons to whom the Software is furnished to do so, subject to | |
the following conditions: |
Open $ vim /etc/default/grub
then add elevator=noop
next to GRUB_CMDLINE_LINUX_DEFAULT
. Run $ update-grub
and $ cat /sys/block/sda/queue/scheduler
to be sure that noop is being used:
$ vim /etc/default/grub
$ update-grub
$ cat /sys/block/sda/queue/scheduler
[noop] deadline cfq
Attention: the list was moved to
https://github.com/dypsilon/frontend-dev-bookmarks
This page is not maintained anymore, please update your bookmarks.
#!/usr/bin/env bash | |
curl https://s3.amazonaws.com/heroku-jvm-buildpack-vi/vim-7.3.tar.gz --output vim.tar.gz | |
mkdir vim && tar xzvf vim.tar.gz -C vim | |
export PATH=$PATH:/app/vim/bin |
Convolutional neural networks for emotion classification from facial images as described in the following work:
Gil Levi and Tal Hassner, Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns, Proc. ACM International Conference on Multimodal Interaction (ICMI), Seattle, Nov. 2015
Project page: http://www.openu.ac.il/home/hassner/projects/cnn_emotions/
If you find our models useful, please add suitable reference to our paper in your work.
Download list_of_surahs_name_in_the_quran.csv file
""" 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 |
# Copyright 2019 Google LLC. | |
# SPDX-License-Identifier: Apache-2.0 | |
# Author: Anton Mikhailov | |
turbo_colormap_data = [[0.18995,0.07176,0.23217],[0.19483,0.08339,0.26149],[0.19956,0.09498,0.29024],[0.20415,0.10652,0.31844],[0.20860,0.11802,0.34607],[0.21291,0.12947,0.37314],[0.21708,0.14087,0.39964],[0.22111,0.15223,0.42558],[0.22500,0.16354,0.45096],[0.22875,0.17481,0.47578],[0.23236,0.18603,0.50004],[0.23582,0.19720,0.52373],[0.23915,0.20833,0.54686],[0.24234,0.21941,0.56942],[0.24539,0.23044,0.59142],[0.24830,0.24143,0.61286],[0.25107,0.25237,0.63374],[0.25369,0.26327,0.65406],[0.25618,0.27412,0.67381],[0.25853,0.28492,0.69300],[0.26074,0.29568,0.71162],[0.26280,0.30639,0.72968],[0.26473,0.31706,0.74718],[0.26652,0.32768,0.76412],[0.26816,0.33825,0.78050],[0.26967,0.34878,0.79631],[0.27103,0.35926,0.81156],[0.27226,0.36970,0.82624],[0.27334,0.38008,0.84037],[0.27429,0.39043,0.85393],[0.27509,0.40072,0.86692],[0.27576,0.41097,0.87936],[0.27628,0.42118,0.89123],[0.27667,0.43134,0.90254],[0.27691,0.44145,0.913 |