For this post I’m going to be giving you all the commands you need to run algorithms through Pacumen. But I will note that the readme file of the Pacumen project does provide some context for you should you choose to play around with the project. You can also reference my exploring testing and AI post for more details on how to use Pacumen. Continue reading Pacumen – Exploring Search Algorithms
Category: Pacumen
Testing Algorithmic Searching, Part 2
This post follows on from the first part. That post, and this one, are building up your understanding of the algorithms that you have to consider when you are a tester in a machine learning or AI environment, particularly when dealing with search problems. Continue reading Testing Algorithmic Searching, Part 2
Testing Algorithmic Searching, Part 1
The next two posts are follow-ons from the previous. The goal here is to get you set up thinking as a tester in a machine learning environment and specifically in the context of search problems. This post, and the next, will focus on making sure you have the basics of the algorithms. Continue reading Testing Algorithmic Searching, Part 1
Testing Learning Systems
Let’s continue the from the last post where you saw a working implementation of a learning environment called Pacumen. Here I want to provide you more details of the basis for this kind of work and use that as a springboard for thinking about how testers fit in these situations. Continue reading Testing Learning Systems
Pacumen – Exploring Testing and AI
In this post I want to set the stage for some future posts regarding thinking about how you might work, as a specialist tester, within the context of an environment that is using machine learning and various artificial intelligence techniques. This is an area that I’m finding many testers are not ready for. To that end, I’m going to show you how to get my Pacumen code repository up and working. Then I’ll take you through a few exercises to put it through its paces. Continue reading Pacumen – Exploring Testing and AI