Linear Regression and Academic Literature: 100 Days of Code (3/100)

Day 3 Of 100 Days of Code Our third day of this 100 Days of Code was filled with in depth analysis of linear regression and elaboration on gradient descent algorithms. What should first be noted is the fact that we successfully published two deeply interwoven articles. The first analyzed in depth linear regression algorithms,Continue reading “Linear Regression and Academic Literature: 100 Days of Code (3/100)”

Linear Regression Models: Topics of Machine Learning

An Introduction to Linear Regression The present article endeavors to explore the intricacies of linear regression models in machine learning. Before embarking on this discussion, we would like to provide a brief overview on the analyses explored in the Topics of Machine Learning series. Much of our investigative efforts have centered on one of twoContinue reading “Linear Regression Models: Topics of Machine Learning”

Confusion Matrix and Measurement of Algorithmic Recall: Topics of Machine Learning

Introduction to the Confusion Matrix The Topics of Machine Learning series has invested a healthy amount of effort in providing the various tools available for amplifying machine learning sophistication. This article follows suit, providing a technique for validating your model’s performance with the implementation of the confusion matrix. Within this Topics of Machine Learning series, we elaboratedContinue reading “Confusion Matrix and Measurement of Algorithmic Recall: Topics of Machine Learning”

Instance and Model-Based Learning: Topics of Machine Learning

Introducing Instance and Model-Based Learning Our series on Machine Learning has elaborated on a variety of topics related to the subject. Firstly, we began by providing an overview to the various machine learning systems that appear in data science, as well as the algorithms associated with these systems. You can explore this overview, which alsoContinue reading “Instance and Model-Based Learning: Topics of Machine Learning”

Supervised Machine Learning Algorithms: Topics of Machine Learning

Introduction to Supervised Machine Learning We now reach a point where we intend to get deeper into the various methodologies of machine learning. Our first article of this series presented all of the general categories of machine learning and their implications. Therein, we documented the various mechanisms and algorithms associated with these categories. They includedContinue reading “Supervised Machine Learning Algorithms: Topics of Machine Learning”