The increased adoption of machine learning (ML) for complex problem-solving and decision-making demands ever-increasing computational resources. The development of recent Large Language Models GPT-…
In data science, Principal Component Analysis (PCA) is a popular technique to reduce the dimension of a dataset. Picture this: data can sometimes be overwhelming with its many dimensions, much like a…
In solving a problem, it is often difficult to obtain the optimal solution due to strict constraints, making it computationally expensive. Lagrange Relaxation is a method that loosens some particular…
"Geometry being useful", I copied that down from this blog. And yes, in any subject, geometry often steps in to offer a fresh perspective. The Convex Hull Trick is a testament to this, seamlessly…