Machine Learning Categories

Machine Learning Categories

1. Supervised Learning

Train the machine using data which is well labeled. For example we need to train the machines to identify vegetables with identification(colors and shapes). Based on that machine can identify vegetables. Here target is very clear.

Supervised learning has two categories

I. Classification

Target/response variables take only descrete(finite/countable) values

Classification Examples


Classification

II. Regression

Target is a continuous variable/can take any real number

Regression Examples


Regression

2. UnSupervised Learning

There is no data to identify the things. Machine has to defferentiate/categoroze the things which are available. For example we have given 4 variaties of dogs and three cats. System is not having data to recognize the dog and cat. But it will identify 4 are same category and 3 are belongs to another category.

3. Deep Learning

Technique to represent a forward step for machine learning. Is like how human brain works.