There is increasing interest in neuro-symbolic methods that combine recent advances in deep learning with symbolic methods of Artifical Intelligence. Yet, at the heart of their integration lies an intriguing puzzle.

Let your application tell you what is going on at critical steps with effective usage of logging. In this post, I talk over a simple setup for using the logging library in Python.

Pylint is a popular linting tool for the Python programming language, and often it needs to be configured. Pylint looks at several different locations to load its configuration.

Thanks to recent libraries such as TensorFlow and PyTorch, deep learning has become so accessible that it now can be in anyone’s toolbox. But at what cost does these libraries reduce the entry level for advanced methods?

I have been using Vim for almost a decade now and this new year I decided to switch to Visual Studio Code. But why?

A short recap of the C programming language with a Pintos perspective as a memory refresher. We go over topics such as preprocessor directives, pointers and linked list structure in Pintos.

You might notice that the in-built Python hash function does not work with dictionaries. That’s for good reason because it can be inconsistent across platforms. In this post, I talk about a simple method using standard libraries to hash a Python dictionary in a more stable manner.

There many methods for handling configuration files within a project and it can be difficult to find a solution that works well. In this post, I talk about a small library that allows argparse to work well across multiple files while still providing the expected argparse features such a help pages.

Sometimes you might want to run unittests from another Python script and gather its results instead of running python3 -m unittest manually. Running test cases programmatically is quite easy and gives you a lot of control on what happens during or after running the test cases.

Spiking neural networks work by simulating the membrane potential of biological neurons. Unlike artificial neural networks spiking ones attempt to model the biological neurons that build up our brains. So while ANNs are inspired by biological brains, SNNs try to create them.