As an AI engineer, monitoring your hardware performance is essential—whether you’re training models on a local Mac or running experiments on a remote GPU server. Two powerful command-line tools hav...

Data visualization is far more than a pretty picture. In high-dimensional spaces (like the 784-dimensional MNIST images), a simple numeric accuracy score doesn’t always reveal which classes might b...

When working in two-dimensional space, we typically start by describing vectors in the “standard basis” (the familiar x-y coordinate system). But there are many situations—especially in linear alge...

Vector projection is a fundamental concept in linear algebra that often appears in machine learning, computer graphics, and physics simulations. By projecting one vector onto another, you find th...

In this blog post, we’ll dive into two fundamental operations in vector analysis: the dot product and projection. We will explain each concept with definitions, geometric interpretations, and a pr...

Artificial Intelligence is changing everything from how we live to how we work and even how we think. It is transforming our lives. As a developer, you should be part of it. And this is the right...

I recently had the pleasure of visiting the Microsoft Headquarters in Redmond, WA, where I reconnected with my old friend Nikola Metulev at the Windows Building on campus. Nikola and I share a dee...

This project was is about training a model on the classic MNIST dataset — a collection of handwritten digits that’s been a staple in the ML community. Let’s take a friendly tour through the code an...

In this post, I’ll walk you through building a simple machine learning pipeline to classify handwritten digits from the MNIST dataset using scikit‐learn. If you’re looking for a beginner-friendly a...

Understanding machine learning often feels like trying to read a secret language hidden in numbers. One way to decode this language is through visualization. A prime example is the MNIST dataset—a ...