In which model the examples are label and the sequence is decided by the teacher
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Types of Machine Learning Algorithms You Should Know

David Fumo
Jun 15, 2017·5 min read

As a request from my friend Richaldo, in this post I’m going to explain the types of machine learning algorithms and when you should use each of them. I particularly think that getting to know the types of Machine learning algorithms is like getting to see the Big Picture of AI and what is the goal of all the things that are being done in the field and put you in a better position to break down a real problem and design a machine learning system.
Terms frequently used in this post:
Labeled data: Data consisting of a set of training examples, where each example is a pair consisting of an input and a desired output value (also called the supervisory signal, labels, etc)
Classification: The goal is to predict discrete values, e.g. {1,0}, {True, False}, {spam, not spam}.
Regression: The goal is to predict continuous values, e.g. home prices.
Types of machine learning Algorithms
There some variations of how to define the types of Machine Learning Algorithms but commonly they can be divided into categories according to their purpose and the main categories are the following:
Supervised learning
Unsupervised Learning
Semi-supervised Learning
Reinforcement Learning
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