Learn how hedonic regression helps estimate factors affecting prices in real estate and consumer goods, aiding in precise ...

From the first 5 rows of the dataset, we can see that there are several columns available: species, island, bill_length_mm, bill_depth_mm, flipper_length_mm, body_mass_g, and sex. There also appears ...

Predicting performance for large-scale industrial systems—like Google’s Borg compute clusters—has traditionally required extensive domain-specific feature engineering and tabular data representations, ...

It shouldn’t come as a surprise if we say Honor is now a major name in the European smartphone market. In fact, the number speaks for themselves. In Q1 2025, the brand achieved a 20% jump in sales and ...

Soon to be the official tool for managing Python installations on Windows, the new Python Installation Manager picks up where the ‘py’ launcher left off. Python is a first-class citizen on Microsoft ...

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: 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: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...

Abstract: In this paper, we consider the problem of learning a linear regression model on a data domain of interest (target) given few samples. To aid learning, we are provided with a set of ...