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What is a neural network?

A neural network is a model that attempts to solve a complex problem by linking different units called neurons. These networks are built on the principle of neural activity, which was developed according to the way the brain works. Neural networks are a type of artificial intelligence used to solve complex tasks. They are widely used in pattern recognition, image recognition, game development and robotics.

What is Deep Learning?

Deep learning is a form of machine learning that uses complex models to analyze very large amounts of data. It is similar in many ways to the learning that the human brain uses to learn new concepts or insights. It is based on a set of algorithms called neural networks. These networks have individual connections that function like synapses in the brain. These connections are then layered to increase the complexity of the patterns they process. Deep Learning is particularly useful for automating processes and developing decision-making systems based on complex data.

What is database architecture?

Database architecture is a branch of computer science that deals with the design, organization and management of databases. It includes the development of database models, the definition of storage structures, the specification of access methods, and the implementation of the database. In addition, database architecture also includes planning and managing the network and system resources required to support the database.

What are cloud technologies?

Cloud technologies are a group of technologies that enable enterprises to access an external, network-based infrastructure to use applications, programs, storage and other resources. They include virtual private networks (VPNs), software-as-a-service (SaaS), infrastructure-as-a-service (IaaS) and platform-as-a-service (PaaS). These technologies enable enterprises to get the resources they need on-demand and flexibly, reducing costs and increasing availability.

What is a Bayes network?

A Bayes network is a special type of probabilistic graph that represents the probability of certain events with respect to other events. It is commonly used in machine learning research and machine learning to model a variety of problems, such as classification, prediction, and structuring of data. It consists of nodes, which represent events, and edges, which represent the relationships between them. A Bayes network can be used to model a set of relationships between events.