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Some commonly used machine learning terms explained.
(in plain English)
(in plain English)
Machine Learning
A subfield of Ai that enables computers to learn with the help of data and make decisions on its own.
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A subfield of Ai that enables computers to learn with the help of data and make decisions on its own.
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Supervised Learning
This is a machine learning technique wherein the dataset is pre-defined. The machine learning model knows what is looking at when it is learning from data.
For example: Classifying numbers from a dataset of labelled images of handwritten digits.
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This is a machine learning technique wherein the dataset is pre-defined. The machine learning model knows what is looking at when it is learning from data.
For example: Classifying numbers from a dataset of labelled images of handwritten digits.
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Unsupervised Learning
As the name suggests, this technique of machine learning is quite the opposite of supervised machine learning. Here the data is unlabelled.
Example: Recommendation systems, classifying people into different customer groups.
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As the name suggests, this technique of machine learning is quite the opposite of supervised machine learning. Here the data is unlabelled.
Example: Recommendation systems, classifying people into different customer groups.
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Reinforcement Learning
Here a model is trained based on the actions of an 'agent'. The agent explores its environment and gets points for doing the right thing and loses points when it does something wrong.
Example: A model learns to play games through trial and error
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Here a model is trained based on the actions of an 'agent'. The agent explores its environment and gets points for doing the right thing and loses points when it does something wrong.
Example: A model learns to play games through trial and error
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Classification
This technique comes under supervised learning, here we assign a label to an input. The output is typically a "yes" or a "no".
Example: Whether a given photo is of a Dog or a Cat.
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This technique comes under supervised learning, here we assign a label to an input. The output is typically a "yes" or a "no".
Example: Whether a given photo is of a Dog or a Cat.
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Regression
This is also a technique that comes under supervised machine learning. It is typically used to find the relation between given data that are related.
A common use case might include predicting the price of a house based on certain parameters.
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This is also a technique that comes under supervised machine learning. It is typically used to find the relation between given data that are related.
A common use case might include predicting the price of a house based on certain parameters.
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Decision Trees
A decision tree is a decision support tool that uses a tree-like model of decisions and their possible consequences.
For example: Predicting the likelihood of survival of someone on the Titanic based on certain parameters.
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A decision tree is a decision support tool that uses a tree-like model of decisions and their possible consequences.
For example: Predicting the likelihood of survival of someone on the Titanic based on certain parameters.
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