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.

In these scenarios, a common approach involves developing both a linear regression model and a logistic classification model with the same dataset and deploying them sequentially. Alternatively ...

In the field of machine learning, linear regression can be considered a type of supervised machine learning. In this use of the method, the model learns from labeled data (a training dataset), fits ...

As well as this, they have identified the most effective features for examining COVID-19 data with linear regression models, which should be of help to bioinformaticians studying datasets where ...

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...

Model building via linear regression models. Method of least squares, theory and practice. Checking for adequacy of a model, examination of residuals, checking outliers. Practical hand on experience ...

It is assumed students have taken at least a first course in linear algebra ... the theory and show how it can be applied to real datasets from finance and insurance including CAPM, and actuarial ...