Introduction

I think I don’t need to mention the fact that like most people, we researchers, or more precisely PhD students are on a budget when considering computer equipment. I can’t speak for other countries, but here in Croatia, as a teaching assistant at a faculty you can expect a decent midrange laptop. For most people that’s great, because most of the PhD students I know, work a lot in the laboratory or do field experiments, and for them, a decent laptop capable of running excel, basic statistical scripts in R and/or Python, some GIS software or AutoCAD is enough.

For quite a time I thought a decent laptop would be great for my research related to Hydrology and Hydrological models. And it was really great, everything worked fast and nice (thanks to an SSD and 16 gigs of RAM). As I started to work with a lot of data, and especially often not really well-formatted (find out how to address this in my other article). At the suggestion of my Mentor and a friend who also worked at a similar position, I more and more started to think that I need to learn programming to shorten boring tasks related to data formatting, copying, etc. I decided to give Python a shot.

Instantly, I got thrilled what a great programming language it is, how easy it makes to do some tasks, on which I usually would waste 3–4 hours in excel. Don’t get me wrong, this is not a blame on excel, by all means it’s GREAT for some fast visualisations, data management or as a simple database. But more and more often I have tasks where a well written and well thought Python script just wins the game and makes life easier.

Let’s get back to the point of this story. When you consume Python and Data Sconce related content online, sooner or later you will stumble across the term “Machine Learning” due to Pythons popularity for such tasks. This is exactly what happened in my case. Pretty fast I got hooked, and started researching more about the topic.

In no time I found myself enrolling the Udacity course “AI Programming with Python Nanodegree”, using the 30 days free access to certain Udacity courses during the lockdown. The final goal of the course is to create an image classifier for flowers. In short, you’ve got an input image, and the code classifies it into one of the defined labels. It took me about one and a half months to pass the course.

When you start with Machine Learning tasks, and Deep Learning in particular, you often find out that some of the “green juice” (NVIDIA GPU 😉) could make your decent midrange laptop or PC a lot faster. Why is that so? The answer is, CUDA cores. Why are they so important, read here in this great article! So, on a budget I started to check the computer enthusiast forums and sites with used parts for second-hand hardware.

I will not provide any test results, this is more an advice type of article, from my perspective and years of experience of buying second hand parts over forums and different sites. I will try to explain what parts can be bought second hand, to save some cash, or get better performance for same money, without taking unnecessary risk.

#deep-learning #cuda #pc #gpu #budget-pc