What are AI algorithms? Artificial Intelligence

1. Artificial Intelligence

At a conference held at Dartmouth in 1956, a group of 10 scientists established the field of artificial intelligence and first introduced the term ‘artificial intelligence’.

1-1. machine learning

It performs functions through field classification and clustering to develop algorithms and technologies that allow computers to learn with

Supervised Learning: Guess the value you want to predict from the training data

Self-learning: Computers learn data on their own without people.

Reinforcement Learning: In a given environment, the agent recognizes the current situation and takes an action, and receives positive and negative rewards accordingly.

1-2. artificial neural network

An algorithm that has problem-solving ability by changing the strength of synaptic bonding through learning in which artificial neurons that form a network through synaptic bonding

1-3. deep learning

Stacking various kinds of artificial neural networks ‘complex’ and ‘very deep’

Among the algorithms related to artificial intelligence, the most common and widely used is pattern recognition.

2. Pattern Recognition

2-1. pattern recognition

What should be preceded in artificial intelligence: recognizing patterns for given data

usage example:

Ø Recognizing license plates at highway tollgates

Ø Diagnose a patient from complex test results

Ø Automatically correct spelling when typing on keyboard on your phone

Ø Decide which ads to show to specific users on your portal

Algorithm Used:

Ø Neighbor Classifier Algorithm

Ø Decision Tree Algorithm

Ø Artificial Neural Network Algorithm

2-2. Nearest Neighbor Classifier Algorithm

· Algorithm for recognizing letters and numbers written by human hands or on car license plates

· Accuracy averages 97%.

Principle:

1-Each of the various shapes of a specific number or character is stored in units of pixels.

At this time, the more various shapes are stored, the higher the accuracy.

2-Enter a specific number or letter

3-Each pixel of the received number and one stored data are selected and compared in units of pixels.

4-If the comparison result is the same, set each pixel to white, otherwise set each pixel to black.

5-Finally, if the same thing (white) is 94%, it is judged to be a correct number, and if the same thing is 70% or less, it is judged not to match the input number.

2-3. kNearest Neighbor Classification Algorithm

Analysis of where a particular voter will vote in an election.

& frequently used in various marketing analysis

 

Original post: https://www.boudy-technology.tn/2022/03/AIAlgorithms.html

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