Automation of human behavior.
AI stands for Artificial Intelligence, which refers to the development of computer systems that can perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and language translation.
Machine learning is a branch of AI that tries to predict outcomes without being programmed explicitly to do so.
For example, by using data and being trained on what an image of a person looks like, an AI through machine learning can try to generate an image of a person.
The “machine” has “learned” to reproduce an image of a person.
There are different methods to get this machine to do so.
Deep learning is a machine learning technique that layers algorithms and computing units—or neurons—into what is called an artificial neural network.
Deep learning is a subset of machine learning that involves the use of neural networks with many layers. These layers allow the network to learn more complex representations of the input data, which can lead to higher accuracy in predicting the desired output. Deep learning has been used in a variety of applications, including image and speech recognition, natural language processing, and autonomous vehicles.
Connections between the inputs of data and the desired output. The rules in between are defined by the machine learning itself during training.
Neural networks are a type of machine learning model that seeks to emulate the structure and function of the human brain. They accomplish this by connecting input data with desired output through a series of nodes, which are connected by weights. During training, the algorithm adjusts these weights to optimize the model's ability to accurately predict the desired output.