Categories: AI/ML Research

A Gentle Introduction to Bayesian Regression

In this article, you will learn: • The fundamental difference between traditional regression, which uses single fixed values for its parameters, and Bayesian regression, which models them as probability distributions.

Building a Logistic Regression Classifier in PyTorch

Logistic regression is a type of regression that predicts the probability of an event. It is used for classification problems and has many applications in the fields of machine learning, artificial intelligence, and data mining. The formula of logistic regression is to apply a sigmoid function to the output of…

March 29, 2023

In "AI/ML Research"

Logistic Regression in OpenCV

Logistic regression is a simple but popular machine learning algorithm for binary classification that uses the logistic, or sigmoid, function at its core. It also comes implemented in the OpenCV library. In this tutorial, you will learn how to apply OpenCV’s logistic regression algorithm, starting with a custom two-class dataset…

December 30, 2023

In "AI/ML Research"

Building a Regression Model in PyTorch

PyTorch library is for deep learning. Some applications of deep learning models are to solve regression or classification problems. In this post, you will discover how to use PyTorch to develop and evaluate neural network models for regression problems. After completing this post, you will know: How to load data…

February 6, 2023

In "AI/ML Research"

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