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Types of Machine Learning
Machine learning is often divided into three categories—Supervised, Unsupervised and Reinforcement Learning.
• Labeled data
• Direct feedback
• Predict outcome, future
Supervised
Learning
• No labels
Machine Unsupervised • No feedback
Learning Learning • 'find hidden structure'
Reinforcement
Learning
• Decision process
• Reward system
• Learn series of actions
Let us discuss them in detail.
Supervised Learning
In supervised learning, you use “labelled” data to train the machine. This means that some data has been marked as
the correct answer. It can be compared to learning in the presence of a supervisor or teacher.
Supervised learning algorithms learn from labelled training data to help predict the outcome of unforeseen data.
Building, expanding, and successfully implementing accurate supervised machine learning models requires time and
technical expertise from a team of highly trained data scientists. Take a look at the examples below:
Example 1:
It is a
mango !
INPUT RAW Supervisor
DATA Training data set Desired Output OUTPUT
Algorithm Processing Model Trained
Model Training
INPUT
Step 1: You provide the system with photos of mangoes and let it know that these are mangoes. This is called
labelled data.
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