Install and setup a virtual environment with Python libraries (including Tensorflow and Keras).You guys should check it out too (especially, if you want to gain expertise in Computer Vision), if you already haven’t. I am just trying to present how I used Adrian’s guide to setup my personal laptop.Īdrian is one of the best experts on Computer Vision and Deep Learning, and I follow his blogs on. The only difference being that Adrian’s guide is focused on setting up a remote system (AWS or another system). This guide heavily follows Adrian Rosebrock’s guide on Setting up Ubuntu 16.04 + CUDA + GPU for deep learning with Python. Create a bootable USB drive with Ubuntu 16 installer.You can follow my earlier blogs to get that done.
The prerequisite to this guide is to have Ubuntu ready on your system. Now, I am using a friend’s system, remotely via SSH, which has a 11 GB Nividia 1080i GPU.
Now, Ubuntu is the only OS on my system, utilizing all of RAM (16 GB), SSD (256 GB), and GPU (Nvidia GeForce 940MX 2 GB).Again, there were limitations to it - the read/write speeds were slow, I couldn’t accommodate large datasets, and occasional “Bus Error”,to name a few. Setup Linux and everything else mentioned in this blog on a USB drive and use it to directly boot my system.I could not utilise 100% of my system hardware and GPU wasn’t accessible at all. This was a good way to get started with coding. Setup a Virtual Machine on Windows and then install Ubuntu and required Python packages.The earlier two types of attempts (I setup the system multiple times in both types) were with reluctance to do away with Windows on my system. I realized the need of it after the 3rd time I was trying to setup my machine.
I am writing this guide so that I can refer back to it whenever I am setting up a Deep learning machine for Computer Vision. How to Setup Ubuntu 16.04 with CUDA, GPU, and other requirements for Deep Learning
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