jrminter

# cvtSpcToMsa.py
#
#   Date      Who  Comment
# ----------  ---  -----------------------------------------------
# 2017-02-01  JRM  Convert spc from a directory to to msa format


import sys
import os
import glob

jrminter

---
title       : My Test of Slidify
subtitle    : My subtitle
author      : John Minter
job         : job line
logo        : M3A-lg.png
framework   : io2012        # {io2012, html5slides, shower, dzslides, ...}
highlighter : highlight.js  # {highlight.js, prettify, highlight}
hitheme     : tomorrow      # 
widgets     : [mathjax]       # {mathjax, quiz, bootstrap}

jrminter

Linear Regression with Factor Variables
========================================================

One of the struggles I have in the Coursera Data Analysis course is
understanding the strengths and weaknesses of the algorithms we have
examined because of the messy data sets chosen ( I appreciate that
real data sets __are__ messy). As a chemist by training, now
specializing in microscopy and image processing, I have repeatedly
learned the benefit of trying out an unfamiliar algorithm on a
well-behaved data set before "going where no one has gone before..."