Write code in the corresponding src/ file for each programming task. Do not change file names — tests depend on them. Commit and push your changes to GitHub. Questions (Do not use conditionals or ...

Implement Linear Regression in Python from Scratch ! In this video, we will implement linear regression in python from scratch. We will not use any build in models, but we will understand the code ...

ABSTRACT: This paper proposes a universal framework for constructing bivariate stochastic processes, going beyond the limitations of copulas and offering a potentially simpler alternative. The ...

ABSTRACT: This paper deals with linear programming techniques and their application in optimizing lecture rooms in an institution. This linear programming formulated based on the available secondary ...

Linear programming (LP) solvers are crucial tools in various fields like logistics, finance, and engineering, due to their ability to optimize complex problems involving constraints and objectives.

Abstract: A novel framework has recently been proposed for designing the molecular structure of chemical compounds with a desired chemical property using both artificial neural networks and mixed ...

Abstract: Coefficients learning has long been challenging in genetic programming based symbolic regression (GPSR). Recent GPSR methods employ Pearson correlation coefficient for fitness assessment ...