I use Python 3 and Jupyter Notebooks to generate plots and equations with linear regression on Kaggle data. I checked the correlations and built a basic machine learning model with this dataset.

A predictive statistical correlation and relationship between the wear rate and the hardness was carried out. A linear and quadratic polynomial regression machine learning details of the factors ...

spopt: spopt is an open-source Python library for solving optimization problems with spatial data. Originating from the original region module in PySAL, it is under active development for the ...

Investment Style Analysis: Python Snippets for Evaluating Style Drift. ... Like before, fit the regression model to the factors in the Morningstar NA Equity Risk Model. ...

The detection of various reactions using computer vision, machine learning, and artificial intelligence is a rapidly growing field of research. In this paper, we present a sentiment analysis model ...

This repository accompanies our GIScience publication "Benchmarking regression models under spatial heterogeneity" (see reference below). In the code base, we provide 1) the script for reproducing our ...

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 ...