Now that we’ve explored the fundamentals of React, it’s time to apply those concepts in a real-world project. A weather app is a perfect next step — simple enough to stay approachable, yet full of opportunities to practice key React…
1. How to Set Up Your React App In the previous post, we explored the core concepts behind React — from components and props to state and hooks. Now it’s time to put that knowledge into action by building a…
Introduction If you’ve ever built web applications using traditional frameworks like ASP.NET Web Forms or MVC, the idea of switching to a JavaScript-based frontend library like React might seem both exciting and intimidating. I’ve been there myself. Coming from a…
Coming from a backend development background, I’ve always been interested in how different layers of an application connect — from data processing and business logic to how information is ultimately displayed to users. My early development experience was rooted in…
1. The Overlooked Game-Changer in ML Projects Imagine two data scientists working on the same problem. One spends weeks fine-tuning hyperparameters, swapping out algorithms, and running endless grid searches. The other starts by methodically selecting the right features, then trains…
Data anomalies are like silent alarms—ignoring them can be catastrophic. A single fraudulent transaction, a failing server, or an abnormal medical reading might seem like minor blips in your dataset, but they often carry serious consequences. Traditional outlier detection methods…
Machine learning (ML) is the science of teaching computers to learn from data without being explicitly programmed. Unlike traditional software, where rules are hard-coded, ML systems improve their performance by identifying patterns and making decisions based on past experiences. In…
1. The Confusion Around AI, Machine Learning, and Data Science If you’ve ever found yourself nodding along to a conversation about Artificial Intelligence (AI), Machine Learning (ML), or Data Science—only to realize you’re not entirely sure how they differ—you’re not alone. These terms…
Every second, LinkedIn’s Kafka infrastructure processes 2.3 million messages—a staggering 7 trillion daily. What makes this possible isn’t just Kafka’s components, but how they’re architected to work in harmony at planetary scale. In my previous post, I introduced Apache Kafka and explained…
The Silent Force Behind Modern Data Imagine ordering a ride on Uber. The app matches you with a driver in seconds, calculates the fare in real time, and updates your route dynamically—all while processing millions of such requests globally at…
