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There are two main types of deep learning models:

u Artificial Neural Networks (ANN) u Convolutional Neural Networks (CNN)

Deep Learning

Artificial Neural Networks Convolutional Neural
(ANN) Networks (CNN)

u Artificial Neural Network (ANN): Artificial Neural Networks can be defined as a computing system made
up of simple, highly interconnected processing elements which process information by their dynamic state
response to external inputs. These are structured to mimic the working of human brain and neurons. ANNs
are useful for solving problems for which the data set is very large.
u Convolutional Neural Network (CNN): The Convolutional Neural Network (CNN) is a multilayer, feed-forward
neural network that uses perceptrons for supervised learning and data analysis. It is used mainly with visual
data, such as image classification. These networks are basically designed to process data through multiple
layers of arrays. CNNs have proven very effective in various areas like image recognition and classification.

Neural Network

A neural network is a series of algorithms that depicts the relationships in a set of data through a process that
mimics the way the human brain operates.

Knowledge Botwledge Bot
Kno
Neurons, or nerve cells, are the fundamental building blocks of the nervous system, responsible for trans-
mitting information throughout the body via electrical and chemical signals, enabling all brain functions
like sensation, movement, thought, memory, and feeling.

Artificial Neural Networks (ANN) refer to the systems of neurons which are artificial in nature. It is ANNs that
serve as a powerful technology in many computer vision applications. These are fast and efficient ways to solve
problems for which the dataset is very large, such as in images recognition and classification.

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