Ryuru 
Data pipelines are cool, but have you ever considered their security? It’s probably a yes, because we’ve been hearing news about unauthorized access to systems and data theft for a long time. So, if you’re in this field, you’ve likely thought about the security of data pipelines at least once. So here you are. Yeah, […]
The Curse of Dimensionality is something that catches a lot of people off guard. More data sounds like a dream: better models, more accurate results, and the potential for big wins. But the reality is that piling on more features and data can backfire. Instead of making things better, it can actually make everything worse, […]
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 […]
I know this article is a bit off-topic from our usual blog content, but I’m really passionate about the Swift programming language and wanted to share my thoughts. Specifically, I want to talk about the future of Swift outside the Apple ecosystem, not just on macOS, iOS, or iPadOS, but in broader areas like server-side […]
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 […]
Data doesn’t just magically become useful. Whether you’re building dashboards, feeding machine learning models, or just trying to get a cleaner look at last quarter’s sales, you need data that’s structured, clean, and actually means something. And that’s where transformation comes in, particularly through ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) processes. But […]
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 […]
Let’s talk about data. It’s everywhere right now, right? The term has become synonymous with the tech boom of the 2020s. But here’s the catch, data isn’t something we just discovered. It’s always been essential. The real shift? How accessible it has become today, thanks to the massive strides in AI and machine learning. Before […]
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 […]