The pitfalls of over-reliance on AI for self-directed learning
Do you over-rely on AI? Understand the risks of using AI for self-directed learning. Struggle productively. Reclaim your critical thinking.
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How Far Can You Push Excel with Regex?
Excel’s regex functions bring pattern recognition and text parsing to the spreadsheet. This article explores how Regex Pattern Matching works under the hood – from formal grammars and finite state machines to practical formulas for cleaning, extracting, and restructuring messy data.
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Convolution, Kernels & Filters: A Beginner’s Guide to Edge Detection
Ever noticed how your brain just knows where one object ends and another begins? That instinctive separation is a fundamental part of how we perceive the world. And computers? Well, they just need a bit more help.
In computer vision, edge detection is the process of teaching machines to recognise those boundaries, outlines, and transitions in intensity that define structure in an image.
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Still copy-pasting into ChatGPT? Here’s how to turn your ideas into AI-powered apps
You’re staring at ChatGPT. You’ve done this a hundred times before: typed a question, copied a response, pasted it into some half-built project or document. Maybe it helped. Maybe it wasn’t quite what you were looking for. But here’s the thing no one tells you: that chat box you’re using? It’s not the product. It’s the demo.
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You’re using ChatGPT wrong. Here’s how to prompt like a pro
Most people treat ChatGPT like a search engine. But with the right mindset and smarter prompting techniques, you can get clearer, more useful responses. This article shows you how.
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22/7 and the Approximation of Irrational Numbers
Irrational numbers are somewhat difficult to work with. Unfortunately, they’re also quite useful and crop up both in pure and applied mathematics, and tons of places you may not expect. When written in decimal form, they result in an infinite sequence of numbers with no apparent pattern. If we round or truncate this number, we lose accuracy and introduce some level of error into any calculation.
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Formal Grammars – The Hidden Mathematics of Language
Languages follow invisible rules we rarely notice—but what if we could describe them with math? This article breaks down formal grammars and shows how they underpin both human language and computer logic.
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Model Evaluation: Why Accuracy Isn’t Enough
Suppose we have a model that predicts the colour of a ball. We have 5 red balls and 5 blue balls and we ask our model to make a prediction of the colour of each of them. How can we evaluate our model’s success?
One approach would be to count the number of predictions that our model gets right. We count the number of red balls that the model predicts to be red (number of True Positives) and count the number of blue balls that our model predicts to be blue (the number of True Negatives). -
Mountains, Cliffs, and Caves: A Comprehensive Guide to Using Perlin Noise for Procedural Generation
Unlock the power of Perlin Noise in procedural terrain creation. Learn how to implement it from scratch, adjust octaves, lacunarity, persistence, and even extract real-world height distributions – to craft mountains, cliffs, and cave systems with precision and creativity.
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From Love to Logic: How Algorithms Decide Our Matches
Explore the Gale-Shapley Algorithm and the Stable Matching Problem. Learn how algorithms create stable pairings, not just perfect matches.
