Introduction to Machine Learning (Part 2)

Machine Learning Type

Since Machine Learning (ML) is one of the Artificial Intelligence (AI) branches, ML also has its branches. ML can be divided into four categories:

  1. Supervised Machine Learning
  2. Unsupervised Machine Learning
  3. Semi-Supervised Machine Learning and,
  4. Reinforcement Machine Learning

 

Each category had its own use cases, but it shared one common goal, which is to achieve the highest prediction in accuracy and precision. 

  1. Supervised Machine Learning - is a ML which learn based on data that is labeled acting as a guidance for the ML to produce outcome. Figure 1 summarize the statement given.


  2. Unsupervised Machine Learning - is a ML which learn independently without and will draw out it's own conclusion based on the trend, pattern, feature etc.


  3. Semi-Supervised Machine Learning - is a ML which combine both Supervised Machine Learning and Unsupervised Machine Learning. This ML learn from data that is labeled and unlabeled where most of the data is unlabeled.


  4. Reinforcement Machine Learning - is a ML which learn based on reward system where every time the ML