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The Road to TensorFlow – Part 1 Linux

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There have been some remarkable advancements in Artificial Intelligence type algorithms lately. I blogged on this a little while ago here. Whether its computers reading hand-writing, understanding speech, driving cars or winning at games like Go, there seems to be a continual flood of stories of new amazing accomplishments. I thought I’d spend a bit of time getting to know how this was all coming about by doing a bit of reading and playing with the various technologies.

I wanted to play with Neural Network technology, so thought the Google TensorFlow open source toolkit would be a good place to start. This led me down the road to quite a few new (to me) technologies. So I thought I’d write a few blog posts on my road to getting some working TensorFlow programs. This might take quite a few articles covering Linux, Python, Python libraries like Pandas, Stock Market technical analysis, and then TensorFlow.


The first obstacle I ran into was that TensorFlow had no install image for Windows, after a bit of Googling, I found you need to run it on MacOS or Linux. I haven’t played with Linux in a few years and I’d been meaning to give it a try.

I happened to have just read about a web site that provides VirtualBox and VMWare images of all sorts of versions of Linux all ready to go. So I thought I’d give this a try. I downloaded and installed VirtualBox and downloaded a copy of 64Bit Ubuntu Linux. Since I didn’t choose anything special I got Canonical’s Unity Desktop. Since I was trying new things, I figured oh well, lets get going.

Things went pretty well at first, I figured out how to install things on Ubuntu which uses APT (Advanced Packaging Tool) which is a command line utility to install things into Ubuntu Linux. This worked pretty well and the only problems I had were particular to installing Python which I’ll talk about when I get to Python. I got TensorFlow installed and was able to complete the tutorial, I got the IDLE3 IDE for Python going and all seemed good and I felt I was making good progress.

Then Ubuntu installed an Ubuntu update for me (which like Windows is run automatically by default). This updated many packages on my virtual image. And in the process broke the Unity desktop. Now the desktop wouldn’t come up and all I could do was run a single terminal window. So at least I could get my work off the machine. I Googled the problem and many people had it, but none of the solutions worked for me and I couldn’t resolve the problem. I don’t know if its just that Unity is finicky and buggy or if it’s a problem with running in a VirtualBox VM. Perhaps something with video drivers, who knows.

Anyway I figured to heck with Ubuntu and switched to Red Hat’s Fedora Linux. I chose a standard simple Gnome desktop and swore to never touch Unity again. I also realized that now I’m retired, I’m not a commercial user, so I can freely use VMWare, so I also switched to VMWare since I wondered if my previous problem was caused by VirtualBox. Anyway installing TensorFlow on Fedora seemed to be quite difficult. The dependencies in the TensorFlow install assume the packages that Ubuntu installs by default and apparently these are quite different that Fedora. So after madly installing things that I didn’t really think were necessary (like the Gnu Fortran compiler), I gave up on Fedora.

So I went back to and downloaded an Ubuntu image with the Gnome desktop. This then has been working great. I got everything re-installed quite quickly and was back to being productive. I like Gnome much better than Unity and I haven’t had any problems. Similarly, I think VMWare works a bit better than VirtalBox and I think I get a bit better performance in this configuration.

I have Python along with all the Python scientific and numerical computing libraries working. I have TensorFlow working. I spend most of my time in Terminal windows and the IDLE3 IDE, but occasionally use FireFox and some of the other programs pre-installed with the distribution.


I’m greatly enjoying working with Linux again, and I’m considering replacing my currently broken desktop computer with something inexpensive natively running Linux. I haven’t really enjoyed the direction Windows has taken after Windows 7 and I’m thinking of perhaps doing most of my computing on Linux and MacOS.


I am enjoying using Linux again. In spite of my initial problems with Ubuntu’s Unity Desktop and then with Fedora (running TensorFlow). Now that I have a good system that seems to be stable and working well I’m pretty happy with it. I’m also glad to be free of things like App stores and its nice to feel in control of my environment when running Linux. Anyway this was the small first step to TensorFlow.

Written by smist08

August 23, 2016 at 11:40 pm

9 Responses

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  1. Are you no more interested sage?
    Does your successor had a blog?

    emil baruch

    August 24, 2016 at 2:56 am

  2. Nice to see you’re still keeping things simple Steve.

    Aslan Kanzas

    August 24, 2016 at 3:16 am

  3. […] is part 2 on my blog series on playing with TensorFlow. Last time I blogged on getting Linux going in a VM. This time we will be talking about the Python programming […]

  4. […] on with my long and winding journey to learn TensorFlow, we started with Linux then went on to Python. Today we will be looking at a number of necessary Python […]

  5. […] series on Google TensorFlow and we still won’t get to TensorFlow in this article. We’ve covered Linux, Python and various Python libraries so far. Last time we started to use Python libraries to load […]

  6. […] now quickly covered a number of preliminary topics including Linux, Python, Python Libraries and some Stock Market theory. Now we are ready to start talking about […]

  7. […] after a long journey through Linux, Python, Python Libraries, the Stock Market, an Introduction to Neural Networks and training Neural […]

  8. […] to household logistics I moved my TensorFlow work over to my MacBook Air from running in an Ubuntu VM image on our Windows 10 laptop. Installing Python 3, TensorFlow and the various other libraries […]

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