TensorFlow

I’ve installed TensorFlow with python and python3 (I am intimate with python2, not so much with python3 but this gives me a little motivation to use 3). A little fumbling around with install package. Had to un-install backports.weakref and then install it to get a version with a needed function for the python2 version.  Then started going through the tutorial and getting started pieces. Those are pretty well written at TensorFlow’s website.  Basically kept record of their notebook in my own Jupyter notebook (TensorFlow Basics). Went though building and testing a linear regression. Then jumped ahead to check that their TensorBoard functionality is working. Work with  TensorFlow being kept in ~/TensorFlowSandbox

Other notes (backfilling here):

Installed Jupyter which I start at commandline as root by “jupyter notebook”

Installed R and RStudio. Historically, I’m more comfortable with CLI interfaces and have shied away from RStudio, but am giving it a chance. Used the opportunity to play with RMarkdown (actually kind of nice) and therein documented playing with their neural net package. RMarkdown allows you to ‘publish’ their notebooks either to RStudioConnect ($) or to Rpubs (Free). So now I have a site (http://rpubs.com/stevevejcik) to keep my RMarkdown notebooks. To let RStudio connect to RStudioConnect/RPubs, required libssl-dev (via apt-get) and PKI (via R) and then reconnect.

Also playing with Shiny. Created a Shiny App and uploaded to https://www.shinyapps.io/.