What is Machine Learning?? Machine learning explained in simple terms | Types of Machine Learning

A machine learning system builds prediction models, learns from previous data, and predicts the output of new data whenever it receives it.
Supervised Learning
In supervised learning, sample labeled data are provided to the machine learning system for training, and the system then predicts the output based on the training data.
The system uses labeled data to build a model that understands the datasets and learns about each one.
After the training and processing are done, we test the model with sample data to see if it can accurately predict the output.
The mapping of the input data to the output data is the objective of supervised learning.
Supervised learning can be grouped further in two categories of algorithms:
Classification,Regression
Examples are Object recognition,spam detetction
Unsupervised Learning
Unsupervised learning is a learning method in which a machine learns without any supervision.
The training is provided to the machine with the set of data that has not been labeled, classified, or categorized.
The algorithm needs to act on that data without any supervision.
The goal of unsupervised learning is to restructure the input data into new features or a group of objects with similar patterns.
The machine tries to find useful insights from the huge amount of data.
It can be further classifieds into two categories of algorithms:
Clustering
Association
Reinforcement Learning
Reinforcement learning is a feedback-based learning method, in which a learning agent gets a reward for each right action and gets a penalty for each wrong action.
After each action, the algorithm receives feedback that helps it determine whether the choice it made was correct, neutral or incorrect.
The agent learns automatically with these feedbacks and improves its performance.
The goal of an agent is to get the most reward points, and hence, it improves its performance.
The robotic dog, which automatically learns the movement of his arms, is an example of Reinforcement learning.