Supervised and unsupervised learning, model evaluation, and applications.
Chapter 1 : Introduction to Machine Learning
Traditional computer programming relies on explicit instruction. A human programmer analyzes a problem, constructs a precise algorithm, and codes logical rules…
Chapter 2 : Introduction to Supervised Learning
Supervised learning is the most widely deployed branch of artificial intelligence in industrial applications. The core principle of supervised learning is simpl…
Chapter 3 : Bayesian and Instance-based Learning
Machine learning algorithms process data under uncertainty, noise, and incomplete information. To build reliable systems, algorithms must quantify uncertainty a…
Chapter 4 : Introduction to un-supervised learning and dimensionality reduction
Machine learning algorithms fall into distinct paradigms based on how they process input data and update their internal parameters. Supervised learning algorith…
Chapter 5 : Measures for Performance Evaluation of ML algorithms
Building predictive models represents only the initial phase of the machine learning workflow. Once an algorithm processes input features and adjusts its intern…