Supervised Learning: Bias Mitigation With Adversarial Training
Supervised learning stands as a cornerstone of modern machine learning, empowering systems to learn from labeled data and make accurate predictions. From spam detection to image recognition, its applications are pervasive and continue to reshape industries. This blog post delves deep into the world of supervised learning, exploring its core concepts, algorithms, practical applications, and the critical considerations for building successful supervised learning models.
What is Supervised Learning?
The Core Concept
Supervised learning is a type of machine learning where an algorithm learns from a labeled dataset. This means that each data point in the dataset is paired with a correct output or "label." The algorithm's goal is to learn a mapping function that can accurately predict the output...