Explain the different domains of Artificial Intelligence.

Different domains of Artificial intelligence(AI)
Somen DasNovember 19, 2020
different domains of artificial intelligence image

Artificial intelligence is a computer system that is able to perform tasks that ordinarily require human intelligence.

Artificial intelligence systems are critical for companies that wish to extract value from data by automating and optimizing processes or producing actionable insights.

There are certain domains of artificial intelligence on which we can create our expertise
Machine learning
Deep learning
Robotics
Expert systems
Fuzzy logic
Natural language processing
Computer vision

1. Machine learning
   machine learning image, robot reading a book

Machine learning is a subset of artificial intelligence.
Machine learning enables computers or machines to make data-driven decisions rather than being explicitly programmed for a certain task.
These programs or algorithms are designed in a way that they learn and improve over time when are exposed to new data.

Different types of machine learning models
Supervised learning
Unsupervised learning
Reinforcement learning
Use cases
Product recommendation on a shopping website.
spam filter on email.
Chatbots

1. Deep learning
   deep learning, robot observing an apple,

Deep learning is artificial intelligence (AI) function that imitates the working of the human brain in processing data and creating patterns for use in decision making.

Deep learning is a subset of machine learning in artificial intelligence that has network capable of learning unsupervised from data that is unstructured or unlabeled also known as deep neural learning or deep neural network.

Different types of deep learning models
Autoencoders
Deep belief net
Convolutional neural network
Recurrent neural network
Reinforcement learning to neural network
Use cases
Driverless vehicles
Virtual assistants
chatbots
Medical research
Facial recognition

1. Robotics
   robot is controlled by remote

Robotics is a branch of engineering that involves the conception, design, manufacture, and operation of robots.
This fields overlaps with electronics, computer science, artificial intelligence, mechatronics, nanotechnology and bioengineering.
Different types of robots
Pr-programmed robots
Humanoid robots
Autonomous robots
Teleoperated robots
Augmenting robots
Use cases
Manufacturing
Logistics
Healthcare
Home

1. Expert system
   expert system, a man operating system

An expert system is a program that uses artificial intelligence technology to simulate the knowledge and judgement of humans.
Expert systems usually include a subject-specific knowledge base and can have additional modules added to expand their capacities.

Different types of expert systems
Rule-based systems
Frame-based systems
Hybrid systems
Model-based systems
Off the shelf systems
Custom made systems
Use cases
In the medical field
In the agriculture field
In the education field

1. Fuzzy logic
   Fuzzy logic image, a robot playing chess

Fuzzy logic is a method of reasoning that resembles human reasoning. The approach of fuzzy logic imitates the way of decision making in humans that involves all intermediate possibilities between digital values yes or no.

The conventional logic block that a computer can understand takes precise input and produces a definite output as true or false which is equivalent to human’s yes or no.

Different types of fuzzifier
Singleton fuzzifier
Gaussian fuzzifier
Trapezoidal or triangular fuzzifier
Use cases
Psychology
Pattern recognition and classifications
Securities
Medical
Marine
Finance

1. Natural language processing
   natural language processing, conversation between men and women

Natural language processing is a branch of artificial intelligence that helps the computers understand interpret and manipulate human language.

Natural language processing draws from many disciplines including computers science and computational linguistics in its pursuit to fill the gap between human communication and computer understanding.

Different types of Natural language processing(NLP)
Optical character recognition
Speech recognition
Machine translation
Natural language generation
Sentiment analysis
Semantic search
Machine learning
Use cases
Email filter
Smart assistants
Search results
Predictive text
Language translation
Digital phone calls
Text analytics

1. Computer vision
   computer vision image

Today, computer vision is one of the hottest subfields of artificial intelligence and machine learning given its wide variety of applications and tremendous potential. It’s a goal to replicate the powerful capacities of human vision.

Computer vision system must recognize the present objects and their characteristics such as shapes textures, colours, sizes, spatial arrangement, among other things to provide a description as complete as possible of the image.

Different techniques of computer vision
Image classification
Object detection
Object tracking
Semantic segmentation
Instance segmentation
Use cases
Defect detection
Metrology
Intruder detection
Assembly verification
Screen reader