Artificial neural networks | Classification algorithms | Neural network architectures | Computational statistics

Types of artificial neural networks

There are many types of artificial neural networks (ANN). Artificial neural networks are computational models inspired by biological neural networks, and are used to approximate functions that are generally unknown. Particularly, they are inspired by the behaviour of neurons and the electrical signals they convey between input (such as from the eyes or nerve endings in the hand), processing, and output from the brain (such as reacting to light, touch, or heat). The way neurons semantically communicate is an area of ongoing research. Most artificial neural networks bear only some resemblance to their more complex biological counterparts, but are very effective at their intended tasks (e.g. classification or segmentation). Some artificial neural networks are adaptive systems and are used for example to model populations and environments, which constantly change. Neural networks can be hardware- (neurons are represented by physical components) or software-based (computer models), and can use a variety of topologies and learning algorithms. (Wikipedia).

Types of artificial neural networks
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Lecture 2A : An overview of the main types of neural network architecture

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From playlist Neural Networks for Machine Learning by Professor Geoffrey Hinton [Complete]

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Lecture 2.1 β€” Types of neural network architectures β€” [ Deep Learning | Geoffrey Hinton | UofT ]

From playlist Neural Networks for Machine Learning β€” Geoffrey Hinton, UofT [FULL COURSE]

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Graph Neural Networks, Session 2: Graph Definition

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πŸ”₯ 𝐌𝐚𝐜𝐑𝐒𝐧𝐞 π‹πžπšπ«π§π’π§π  π„π§π π’π§πžπžπ« 𝐌𝐚𝐬𝐭𝐞𝐫𝐬 𝐏𝐫𝐨𝐠𝐫𝐚𝐦 : https://www.edureka.co/masters-program/machine-learning-engineer-training (Use Code "π˜πŽπ”π“π”ππ„πŸπŸŽ") This Edureka video on "Artificial Intelligence Full Course" will provide you with a comprehensive and detailed knowledge of Artificial Intelligence

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