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Artificial intelligence – raw data is treated like a train set and a test set during AI and machine learning algorithms building. Raw data is used for profiling and personalization to customize user profiles [6] and divide them for segmentation, e.g., per gender or location (based on data point). Business intelligence – raw
Data communication, including data transmission and data reception, is the transfer of data, transmitted and received over a point-to-point or point-to-multipoint communication channel. Examples of such channels are copper wires , optical fibers , wireless communication using radio spectrum , storage media and computer buses .
Machine learning and data mining often employ the same methods and overlap significantly, but while machine learning focuses on prediction, based on known properties learned from the training data, data mining focuses on the discovery of (previously) unknown properties in the data (this is the analysis step of knowledge discovery in databases).
Data compression aims to reduce the size of data files, enhancing storage efficiency and speeding up data transmission. K-means clustering, an unsupervised machine learning algorithm, is employed to partition a dataset into a specified number of clusters, k, each represented by the centroid of its points. This process condenses extensive ...
An artificial neural network is an interconnected group of nodes, inspired by a simplification of neurons in a brain.Here, each circular node represents an artificial neuron and an arrow represents a connection from the output of one artificial neuron to the input of another.
Machine learning can be considered a subfield of computer science and statistics. It has strong ties to artificial intelligence and optimization, which deliver methods, theory and application domains to the field. Machine learning is employed in a range of computing tasks where designing and programming explicit, rule-based algorithms is
A foundation model, also known as large X model (LxM), is a machine learning or deep learning model that is trained on vast datasets so it can be applied across a wide range of use cases. [1] Generative AI applications like Large Language Models are often examples of foundation models.
Data cap; Data Cap Integrity Act; Data circuit-terminating equipment; Data dissemination; Data link; Data over signalling; Data Radio Channel; Data-rate units; Data signaling rate; Data-dependent jitter; Datex code; Degree of isochronous distortion; Degree of start-stop distortion; Differential coding; Digital Audio Access Protocol; Digital ...