Machine Learning is just another way of human knowledge acquisition. It expands the human cognition beyond biological boundaries, from computation to discovery and even to creativity.
Machine Learning algorithms are the key components for understanding knowledge hidden in large datasets.
They come in two flavors:
1. Supervised – regression or classification models that are driven by a certain objective; for instance classify if an item is positive or negative
2. Unsupervised – typically clustering algorithms that create groups of similar objects
Two different approaches are common for the generation of Machine Learning models:
1. Discriminative Models
2. Generative Models