this table shows different types of examples for CNN data formats

Examples of different formats of data in CNN

For CNNs, the data used usually has several channels (single channel or multichannel)  with different dimensionalities (1-D, 2-D, or 3-D). Each of these channels represent an observation of a different quantity at some point in space or time.

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South Dakota State University

Data refers to facts, figures, or information collected and used for analysis, reference, or computation. It can be qualitative or quantitative, and it's the basis for reasoning, discussion, or calculation in various contexts, such as scientific research, business analysis, and technological processes. Data can be in various forms, including numbers, text, images, or sounds, and it's often processed and analyzed to derive meaningful insights or decisions.

Data

Goodfellow, I., Bengio, Y., & Courville, A. (2016). $\mathit{Deep \ Learning.}$ MIT Press. Retrieved from [www.deeplearningbook.org](https://www.deeplearningbook.org) 

Deep Learning

Structured data is comprised of clearly defined data types whose pattern makes them easily searchable. Data may be human or machine generated as long as the data is created within an RDBMS structure. This format is eminently searchable both with human generated queries and via algorithms using type of data and field names, such as alphabetical or numeric, currency or date.

Structured Data

Unstructured data either does not have a pre-defined data model or is not organized in a pre-defined manner. It has internal structure but is not structured via pre-defined data models or schema. Unstructured data may be textual or non-textual, and human- or machine-generated. It may also be stored within a non-relational database like NoSQL.

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