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Artificial Intelligence VS Machine learning VS Deep learning | by Iqra Mahmood | Sep, 2022

admin by admin
September 10, 2022
in Machine Learning


Artificial intelligence MACHINE LEARNING Deep LEARNING

Artificial intelligence is the ability of a machine to mimic human behavior. Machine Learning is a subset of artificial intelligence. Deep Learning is a subset of machine learning

AI VS ML VS DL
AI VS ML VS DL

Artificial intelligence is the common term for technology that has been designed to solve some of the most serious problems of humankind, from pollution to climate change. It is used to solve the problems just like the human brain.
In AI, we provide data and set the rules for the ai system, and draw the output from it. First rules are applied to the data and then we draw the conclusion or output from it.

Just like the Snake game, we start from a single point and set the rules to play the game. The game ends when the snake either moves off the screen or moves into itself. The output will be a game end or snake grows.

Artificial intelligence involves Data -> Rules -> Output” class=”ce jp jq” src=”https://miro.medium.com/max/300/1*sEcFIcxAV-mR5hBt6rxckg.png 300w” sizes=”” loading=”lazy”/></div>
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Machine learning (ML) is a type of artificial intelligence and computer science that concentrates on the use of data and algorithms to mimic the way that humans learn, gradually improving its accuracy.

Algorithms are trained to make classifications or predictions and to find key insights in data mining projects. These insights subsequently guide decision-making within applications and businesses, impacting key growth metrics.

In Machine learning (also referred to as predictive analytics), We extract rules from data based on data structure so we will first give the answers to it, and then predict the output based on the pattern drawn from the data.

Data + Answers -> Machine learning” class=”ce jp jq” src=”https://miro.medium.com/max/300/1*nLUFa6xe8_ZhLvk2w-URMw.png 300w” sizes=”” loading=”lazy”/></div>
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Deep learning involves a neural network in which we trained neural networks from single layer to multilayer. It provides more accurate results as compared to machine learning.

Suppose we want to buy a house, we have some features as it must be near the school, it must have three bedrooms and have good neighbors. We want to predict the house price based on these three features. If we get the price on basis of these three parameters’ relation then this will be an example of deep learning.

AI takes rules

ML extract rules

DL uses a layered representation of data

Stay tuned for more such articles!!!



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