mlgill

<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.1.1/jquery.min.js">
</script>
<script>
$(document).ready(function(){
  var all_cells = $("div.cell");
  $.each(all_cells, function( index, value ) {
    if ($(value).find("h1").length == 0){
      $(value).hide()
    } else{
      var bare_h1 = $(value).find("h1").text()

mlgill

# Remove all exited containers
docker rm `docker ps -a -q --filter status=exited` 2>/dev/null

# Remove any orphaned containers related to "INSERT_CONTAINER_NAME_HERE"
docker rm `docker ps -a -q --filter ancestor=INSERT_CONTAINER_NAME_HERE` 2>/dev/null

# Remove any orphaned images from aborted/old builds
docker rmi `docker images -q -f "dangling=true"` 2>/dev/null

# Clean up whatever disk-hogging stuff Docker leaves lying aroung

mlgill

class AMSgrad(Optimizer):
    """AMSGrad optimizer.

    Default parameters follow those provided in the Adam paper.

    # Arguments
        lr: float >= 0. Learning rate.
        beta_1: float, 0 < beta < 1. Generally close to 1.
        beta_2: float, 0 < beta < 1. Generally close to 1.
        epsilon: float >= 0. Fuzz factor.

mlgill

#!/bin/bash

####################################################################################
## AWS GPU Instance Setup Script                                                  ##
## Michelle L. Gill                                                               ##
## michelle@michellelynngill.com                                                  ##
## Gist location: https://gist.github.com/mlgill/63114af65d9dd3e1c386b03a02c199b7 ##
## Date updated: 2017/05/27                                                       ##
####################################################################################

mlgill

#! /usr/bin/env python

"""
Solve linear system using LU decomposition and Gaussian elimination
"""

import numpy as np
from scipy.linalg import lu, inv

def gausselim(A,B):

mlgill

Automated Conda Setup

Michelle L. Gill
Updated: 2017/05/20

Regularly updated Gist located here.

This bash script will download and setup a Conda environment on Mac OS X or Linux using a specified Python version (2.7, 3.6) and packages. The Conda installation path and environment name can also be specified. All settings are input at the beginning of the script (see below).

If the Conda directory exists and can be determined to be a Conda installation, a new environment will be created. If the directory does exist but does not appear to be a Conda installation, the script will quit to avoid accidentally overwriting a file.

mlgill

var utils = require('utils'),
    fs = require('fs'), tweet_account_name,
    nbLinks, outputfilename,
    header = "Tweet,Timestamp",
    stream, css, count = 0, images,
    casper = require('casper').create({
        viewportSize: {
            width: 480,
            height: 360
        },

mlgill

#!/usr/bin/env zsh

# set Linux/Darwin url
if [[ `uname` == "Darwin" ]]; then
    echo "Detected Mac OS X..."
    url="http://repo.continuum.io/miniconda/Miniconda3-latest-MacOSX-x86_64.sh"
else
    echo "Detected Linux..."
    url="http://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh"
fi

mlgill

# taken from http://www.piware.de/2011/01/creating-an-https-server-in-python/
# generate server.xml with the following command:
#    openssl req -new -x509 -keyout server.pem -out server.pem -days 365 -nodes
# run as follows:
#    python simple-https-server.py
# then in your browser, visit:
#    https://localhost:4443

import BaseHTTPServer, SimpleHTTPServer
import ssl

mlgill

Keybase proof

I hereby claim:

• I am mlgill on github.
• I am mlgill (https://keybase.io/mlgill) on keybase.
• I have a public key whose fingerprint is 64D5 7A40 E2C2 1E49 EF96 F194 E45F 4767 96F8 74BB

To claim this, I am signing this object: