Machine Learning is the study of an algorithm that takes past and present data and produces the prediction base correct result. We also define ML is an application of AI which provide the ability to automatically learn and produce a result using past and present data set.
Types of Machine Learning
Machine Learning uses statistics to extracting knowledge from data. Regression analysis and Bayesian statistics are important in ML.
1. Supervised Machine Learning
Supervised Learning is used the pictorial data to produce the result. It uses yes/no, true /false logic. Example: Input: Dog Data set Output: German Shepherd dog.
In this type of learning, there are no labels or correct outputs. in this type of ML, the analysis uses the dataset structure.
Reinforcement Learning uses working conditions, situations, etc.
Example: Self-Driving Car