I just finished my Swift article and now I’m releasing another post about the Apple ecosystem. However, that doesn’t mean I’ll be focusing on the Apple ecosystem the whole time; I just wanted to provide an overview of Apple’s AI privacy methods. Apple’s private cloud computing isn’t something new, but it’s also not an old […]
Machine learning models are omnipresent, powering recommendation systems, fraud detection, medical imaging, and more. However, while we obsess over accuracy and performance, we often overlook a critical aspect: security. ML models are vulnerable to hacking (as expected), poisoning, reverse-engineering, and exploitation. Alarmingly, many engineers remain unaware of these threats. Therefore, we prepared this article to […]
The model had all the right ingredients: clean training data, carefully selected features, and performance metrics that looked solid on paper. It was designed to predict user retention, and in a controlled evaluation setting, it performed well. But in production, cracks started to appear. Power users were being misclassified as likely to churn. Casual users […]
Let’s be honest. Few things are more misleading in machine learning than a model showing 99% (or even 100%) accuracy because of overfitting. On paper, that number looks great. But just like a first date that feels a little too perfect, something usually feels off. And most of the time, it is. That shiny accuracy […]
Netflix is undoubtedly one of the biggest streaming platforms in 2025. Today, we will examine how Netflix’s recommendation system works, along with other similar algorithms that analyze your data and predict your preferences. This article is designed to be beginner-friendly and does not contain detailed technical content. It can be easily understood by everyone without […]