Khushi Keswani

Convolutional Neural Networks (CNNs) are a special kind of deep‑learning model designed for data that has a grid‑like structure, such as: 1D grid: Time series, audio signals. 2D grid: Images. 3D grid: Videos (2D + time). Because of this, CNNs are now the go‑to backbone for most computer vision tasks, including image classification, object detection, segmentation, and even modern vision‑language models. Before we dive into the math, let’s briefly trace how the idea of “seeing” evolved, from real cameras...

Brute Force vs Optimized Approaches with Time Complexities in C++ & Python. Approaching number problems requires a certain mindset. At first glance, concepts like reversing a number, checking for primes, or finding the greatest common divisor may feel like things we’ve known since school. But when we try to make a computer understand and solve these, especially in competitive programming, the real challenge emerges. Suddenly, edge cases, time complexity, and efficiency come into play and honestly, that c...

Most of us in data science spend our time building models, tuning hyperparameters, and chasing performance metrics… But there’s one vital step that often gets skipped: Checking the distribution of your data. Yep, before you fit a single model, you need to understand how your data is spread. Why? Because skewed data can skew your model. And your mind, too. What is Data Distribution? Data distribution describes how values in a dataset are spread. It tells you: Where your data clusters If it’s balanced or ...