Machine Learning notes for Andrew Ng on Coursera
These are my personal notes for the " Machine Learning" Coursera course given by Andrew Ng (ex Google Brain). I want to learn more and understand this domain better. Week 1 Topic 1 - Supervised vs Unsupervised machine learning Machine learning as the field of study that gives computers the ability to learn without being explicitly programmed Two main types of machine learning: 1. supervised learning - the data comes with both x input and y output regression: a type of supervised learning: to predict a number from infinitely many possible numbers classification: another type of supervised learning: has a small finite number of outputs (categories) predicted 2. unsupervised learning - the data comes with inputs x but not y, algorithm has to find structure/pattern in the data clustering algorithm: takes data and groups into categories anomaly detection: dimensionality reduction: Supervised learning Regression supervised machine learning Refers to algorithms that learn x to y