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

daroczig

#' Connect and query Imapala via SSH and Impala-shell
#' @param query SQL query to run
#' @param host server hostname or IP
#' @param log enable or disable logging of debug/trace messages
#' @return data.table object
#' @export
query_impala <- function(query, host = 'localhost', log = require(futile.logger)) {

    ## measure time of query
    timer <- proc.time()

lucacerone

#!/usr/bin/env bash
# Compress a pdf using gs. 
# Requires in input the compression type, the name of the file to compress and the name of the output file (in this order).
# Example:
# pdfcompress screen MyHighResDocument.pdf MyLowResDocument.pdf
#
# Possible values for compression types are:
# screen , selects low-resolution output similar to the Acrobat Distiller “Screen Optimized” setting.
# ebook , selects medium-resolution output similar to the Acrobat Distiller “eBook” setting.
# printer , selects output similar to the Acrobat Distiller “Print Optimized” setting.

gabraganca

{%- extends 'full.tpl' -%}

{% block input_group -%}
<div class="input_hidden">
{{ super() }}
</div>
{% endblock input_group %}

{%- block header -%}
{{ super() }}

jexchan

Multiple SSH Keys settings for different github account

create different public key

create different ssh key according the article Mac Set-Up Git

$ ssh-keygen -t rsa -C "[email protected]"

rduplain

"Plot a PNG using matplotlib in a web request, using Flask."

# Install dependencies, preferably in a virtualenv:
#
#     pip install flask matplotlib
#
# Run the development server:
#
#     python app.py
#

wilsaj

from flask import Flask, make_response
app = Flask(__name__)

@app.route("/simple.png")
def simple():
    import datetime
    import StringIO
    import random

    from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas