Riley Rudd - Blogs

Understanding Classification Metrics: ROC, PR, and Confusion Matrix

machine learning

Classification is a supervised, meaning labels are given, learning method where a model attempts to predict the correct label of a given input data sample. The models are…

Unmasking Anomalies: A Deep Dive into Outlier Detection in Machine Learning

machine learning

Anomalies, by definition, are data points that deviate significantly from the majority of the dataset. Detecting these outliers is crucial in fields such as fraud detection…

Linear Regression in Machine Learning: Finding Predictive Relationships

machine learning

Linear regression, a statistical model, serves as a fundamental tool for comprehending the correlation between input and output numerical variables. This model becomes…

Unveiling the Power of Clustering in Machine Learning

machine learning

Clustering is a type of unsupervised learning method, meaning conclusions are drawn about datasets without labeled responses. It is done by grouping a particular set of…

Understanding the Foundations: Probability Theory and Random Variables in Machine Learning

machine learning

Probability theory is the mathematical study of uncertainty, quantifying uncertainty about the world. It is important to understand as a basis to machine learning, because…