karpathy

""" 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

wangruohui

In this article, I will share some of my experience on installing NVIDIA driver and CUDA on Linux OS. Here I mainly use Ubuntu as example. Comments for CentOS/Fedora are also provided as much as I can.

Table of Contents

• Install NVIDIA Graphics Driver via apt-get
• Install NVIDIA Graphics Driver via runfile
  • Remove Previous Installations (Important)
  • Download the Driver
  • Install Dependencies
  • Creat Blacklist for Nouveau Driver

• Stop lightdm/gdm/kdm

ziadoz

#!/usr/bin/env bash
# https://developers.supportbee.com/blog/setting-up-cucumber-to-run-with-Chrome-on-Linux/
# https://gist.github.com/curtismcmullan/7be1a8c1c841a9d8db2c
# https://stackoverflow.com/questions/10792403/how-do-i-get-chrome-working-with-selenium-using-php-webdriver
# https://stackoverflow.com/questions/26133486/how-to-specify-binary-path-for-remote-chromedriver-in-codeception
# https://stackoverflow.com/questions/40262682/how-to-run-selenium-3-x-with-chrome-driver-through-terminal
# https://askubuntu.com/questions/760085/how-do-you-install-google-chrome-on-ubuntu-16-04

# Versions
CHROME_DRIVER_VERSION=`curl -sS https://chromedriver.storage.googleapis.com/LATEST_RELEASE`

matt-bertoncello

# define base image as python slim-buster.
FROM python:3.7-slim-buster as base

## start builder stage.

# this is the first stage of the build.
# it will install all requirements.
FROM base as builder

# install all packages for chromedriver: https://gist.github.com/varyonic/dea40abcf3dd891d204ef235c6e8dd79

korakot

# authenticate
from google.colab import auth
auth.authenticate_user()
import gspread
from oauth2client.client import GoogleCredentials as GC
gc = gspread.authorize(GC.get_application_default())
# create, and save df
from gspread_dataframe import set_with_dataframe
title = 'New Sheet'
gc.create(title)  # if not exist

wch

m <- matrix(1:12, nrow=3)

# Double every element
# ===================

# Method 1: nested for loop
for(i in seq_len(nrow(m))) {
  for(j in seq_len(ncol(m))) {
    m2[i, j] <- m[i, j] * 2
  }

mjdietzx

#!/bin/bash

# install CUDA Toolkit v8.0
# instructions from https://developer.nvidia.com/cuda-downloads (linux -> x86_64 -> Ubuntu -> 16.04 -> deb (network))
CUDA_REPO_PKG="cuda-repo-ubuntu1604_8.0.61-1_amd64.deb"
wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/${CUDA_REPO_PKG}
sudo dpkg -i ${CUDA_REPO_PKG}
sudo apt-get update
sudo apt-get -y install cuda

mbostock

license: gpl-3.0

mikesmullin

sudo apt-get install unzip;
wget -O /tmp/chromedriver.zip http://chromedriver.googlecode.com/files/chromedriver_linux64_19.0.1068.0.zip && sudo unzip /tmp/chromedriver.zip chromedriver -d /usr/local/bin/;

jimmysitu

morningstar.com API

• Get key ratio, return csv format file

http://financials.morningstar.com/ajax/exportKR2CSV.html?t=<market>:<stock>

Market

• XHKG: Hong Kong Stock Exchange
• XASE: American Stock Exchange
• XNAS: Nasdaq Stock Exchange >* XNYS: New York Stock Exchange