What is machine learning

In this chapter, you will learn about what is machine learning and how it can be used in the real world. Let’s understand machine learning in a simple definition.

Machine Learning:
Machine Learning is the practice of studying and using the computer algorithms which gives an ability to the system to automatically learn and improve from experience without being explicitly programmed. This process may starts from,

1. Parsing the existing data
2. Learn from it, it starts with observation or data
3. Make a determination or prediction about something in the world

The machine learning approaches can be categorized into following

1. Supervised Learning
2. Unsupervised Learning
3. Semi-Supervised Learning

Supervised Learning:
The computer is presented with example inputs and their desired outputs, given by a “teacher”, and the goal is to learn a general rule that maps inputs to outputs

Unsupervised Learning:
No labels are given to the learning algorithm, leaving it on its own to find structure in its input. Unsupervised learning can be a goal in itself (discovering hidden patterns in data) or a means towards an end (feature learning).

Semi-Supervised Learning:
A computer program interacts with a dynamic environment in which it must perform a certain goal (such as driving a vehicle or playing a game against an opponent) As it navigates its problem space, the program is provided feedback that’s analogous to rewards, which it tries to maximise.