mattmcd

from subprocess import run
import sympy as sp


def print_to_file(fname, expr):
    # See https://tex.stackexchange.com/questions/34054/tex-to-image-over-command-line/34058#34058
    t_start = r"""\documentclass[border=2pt]{standalone}
\usepackage{amsmath}
\usepackage{varwidth}
\begin{document}

mattmcd

{
  "verbs" : ["aggregate", "architect", "benchmark", "brand", "cultivate", "deliver", "deploy", "disintermediate",
              "disrupt", "drive", "e-enable", "embrace", "empower", "enable", "engage", "engineer", "enhance",
              "envisioneer", "evolve", "expedite", "exploit", "extend", "facilitate", "generate", "grow", "harness", "implement", "incentivize", "incubate", "innovate", "integrate",
              "iterate", "leverage", "matrix", "maximize", "mesh", "monetize", "morph", "optimize", "orchestrate", "productize", "recontextualize", "redefine", "reintermediate",
              "reinvent", "repurpose", "revolutionize", "scale", "seize", "strategize", "streamline", "syndicate", "synergize", "synthesize", "target",
              "transform", "transition", "unleash", "utilize", "visualize", "whiteboard"],
  "adjectives": ["24/365", "24/7", "B2B", "B2C", "back-end", "best-of-breed", "bleeding-edge", "bricks-and-clicks", "clicks-and-mortar",
                  "collaborative", "compelling", "cross-p

mattmcd

import sympy as sp 
x = sp.symbols('x', real=True)
p, q = sp.symbols('p q', positive=True)
KL = sp.Integral(p*sp.log(p) - p*sp.log(q), (x, -sp.oo, sp.oo))
mu, mu1, mu2 = sp.symbols('mu mu1 mu2', real=True)
sig, sig1, sig2 = sp.symbols('sig sig1 sig2', positive=True)
n = 1/sp.sqrt(2*sp.pi*sig**2)*sp.exp(-(x - mu)**2/(2*sig**2))
KL_n = sp.simplify(
    KL.subs({p: n.subs({mu: mu1, sig: sig1}), q: n.subs({mu: mu2, sig: sig2})}).doit()    
)

mattmcd

import boto3
import os
import sys
import zipfile

HERE = os.path.dirname(os.path.realpath(__file__))


def library_install():
    """Dynamically add libraries to path, retrieving from S3 if necessary

mattmcd

FROM amazonlinux:latest

MAINTAINER Matt McDonnell "[email protected]"

RUN yum -y -q update

RUN yum -y -q install python27-pip zip

RUN pip install -q virtualenv

mattmcd

# Amazon #Sagemaker instance
# open Jupyter
# new terminal
cd SageMaker
git clone https://github.com/matterport/Mask_RCNN.git
git clone https://github.com/waleedka/coco.git
cd coco/PythonAPI
source activate tensorflow_p36
make
python setup.py install

mattmcd

import pystan
import numpy as np

# Two compartment model from
# "Stan: A probabilistic programming language for
#  Bayesian inference and optimization" Gelman, Lee, Guo (2015)
# http://www.stat.columbia.edu/~gelman/research/published/stan_jebs_2.pdf

a = np.array([0.8, 1.0])
b = np.array([2, 0.1])

mattmcd

Keybase proof

I hereby claim:

• I am mattmcd on github.
• I am mattmcd (https://keybase.io/mattmcd) on keybase.
• I have a public key ASC3HfvXMCZ-vnJ4gWwCe_hsgtgEHRNrV2qtHOK8iU40Bgo

To claim this, I am signing this object:

mattmcd

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": [
                "s3:PutObject",
                "s3:ListAllMyBuckets",
                "s3:ListBucket",
                "s3:CreateBucket"

mattmcd