If you’ve ever tried to explain Bayes’ theorem to someone at a party, you know the look you get. That glazed-over, polite nod that says “I’ll remember your name but…
You know how some people like to claim that the math we learn in high school has no real-world use? That it’s just a bunch of abstract equations you’ll never…
Lately, I have been working on a project that involves sending images, captured by an industrial camera, from one station to another. The task itself is trivial, however, if the…
Derivatives are a crucial concept in machine learning. It is a mathematical technique to optimize the model's parameters to reduce the cost on every iteration and is widely used in…
When we work with images and real-world objects, we want to collect their coordinates and project them onto a plane for simplification. Such applications are useful in areas like self-driving…
"Optimization is at the heart of machine learning. It is the process of searching through a space of possible models to find one that performs well on a task. It…
Many of us may find understanding statistics a challenging task. Moreover, when it comes to conditional probability, we may find ourselves scratching our heads. And yes, I am one of…
"Machine learning is not magic; it's just a tool, like a hammer or a wrench. And like any tool, it has limitations, which you need to understand in order to…
In this previous post on matrix multiplication, I discussed the geometrical significance of the dot product of matrices and how it represents the linear mapping of vectors. We also realized…
In my last blog on orthogonal projection, I shared how visualizing mathematical concepts help us understand them better. So, I thought of doing the same with matrix multiplication. Matrix multiplication…
