Who is a data scientist? What does he do? What steps are involved in executing an end-to-end data science project? What roles ...

Abstract: Mixed linear regression (MLR) models nonlinear data as a mixture of linear components. When noise is Gaussian, the Expectation-Maximization (EM) algorithm is commonly used for maximum ...

This C library provides efficient implementations of linear regression algorithms, including support for stochastic gradient descent (SGD) and data normalization techniques. It is designed for easy ...

This is a machine learning-based web application built with Flask that predicts the estimated salary of an individual based on their: Years of Experience Education Level Location Previous Salary The ...

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 ...

In this video, we will implement Multiple Linear Regression in Python from Scratch on a Real World House Price dataset. We will not use built-in model, but we will make our own model. This can be a ...

Abstract: In this paper, a hardware design based on the field programmable gate array (FPGA) to implement a linear regression algorithm is presented. The arithmetic operations were optimized by ...

With the accelerating pace of urbanization, air pollution has emerged as a critical global challenge, where ozone (O 3) concentration dynamics have become a pivotal indicator of atmospheric quality ...