Stochastic Gradient Descent Algorithms: Topics of Machine Learning

Introduction to Stochastic Gradient Descent Our previous articles investigated the importance of linear regression and batch gradient descent in machine learning modeling, as well as the intricacies of Gradient Descent models. With respect to gradient descent, here we investigate linear regression as it relates to stochastic gradient descent machine learning. Before embarking on this discussion,Continue reading “Stochastic Gradient Descent Algorithms: Topics of Machine Learning”

Batch Gradient Descent Algorithms: Topics of Machine Learning

Introduction to Batch Gradient Descent Our previous article investigated the importance of linear regression in machine learning modeling, as well as the intricacies of Gradient Descent models. With respect to gradient descent, here we investigate linear regression as it relates to batch gradient descent machine learning. Before embarking on this discussion, we would like toContinue reading “Batch Gradient Descent Algorithms: Topics of Machine Learning”

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”

Multi-Class Classification and Literature: 100 Days of Code (2/100)

Day 2 Of 100 Days of Code We are now underway in this journey of better understanding this coding ecosystem we inhabit. If you’ve followed along the Art of Better Programming thus far, you are well aware that our primary focus to date has been a thorough elaboration on the implementation of machine learning modelsContinue reading “Multi-Class Classification and Literature: 100 Days of Code (2/100)”

Multi-Class Classification In Machine Learning: Topics of Machine Learning

Introduction to Multi-Class Classification Previous Efforts of Machine Learning Series The Topics of Machine Learning series took a bit of hiatus to explore performance measures after examining the various performance measures to quantify efficiency of machine learning models. This particular deviates from this tune to explore multi-class classification. Briefly, thus far in the Topics of Machine Learning series, weContinue reading “Multi-Class Classification In Machine Learning: Topics of Machine Learning”

The ROC Curve in Measuring Algorithmic Performance: Topics of Machine Learning

Introduction to the ROC Curve Previous Efforts The Topics of Machine Learning series has steadily moved from overarching principles of machine learning models to the bits and pieces which drive these models to function. With our previous article having investigated the implementation of the confusion matrix and the role of precision and recall, we now move toContinue reading “The ROC Curve in Measuring Algorithmic Performance: 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”

Differentiating Batch and Online Learning: Topics of Machine Learning

Introduction to Batch and Online 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, whichContinue reading “Differentiating Batch and Online Learning: Topics of Machine Learning”

Unsupervised Machine Learning Models: Topics of Machine Learning

Introduction to Unsupervised Machine Learning Our initial article on this subject introduced our presently comprehensive machine learning series. This article provided an overview to all the various machine learning systems and the functions they execute. The machine learning models extrapolated on therein include supervised, unsupervised, batch, online, instance-based, and model-based learning methodologies. Our subsequent articlesContinue reading “Unsupervised Machine Learning Models: 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”

An Overview Of Machine Learning Systems: Topics of Machine Learning

An Introduction to Machine Learning Systems This article marks the commencement on our series pertaining to machine learning and the learning mechanisms thereof. In order to make discussion of those learning mechanisms, we must first supply reason and logic to the topic at hand. Particularly, we must answer the question: “What exactly is machine learning?”Continue reading “An Overview Of Machine Learning Systems: Topics of Machine Learning”