Semi-structured data is data that is not captured or formatted by traditional methods. Semi-structured data does not follow the format of a tabular data model or relational databases because it does not have a fixed schema. However, the data is not completely raw or unstructured and has some structural elements, such as labels and organizational superdata, which will facilitate its analysis. The advantages of semi-structured data are that they are more flexible and simpler to scale compared to structured data.
Data Fabric is a data architecture that aims to create an integrated structure between different data sources.
In the field of artificial intelligence and machine learning, various sampling methods are used to generate new data using the information learned by the models.
Fine-tuning is the process of optimizing a pre-trained model for a specific task. This method is an important part of the approach known as transfer learning and is widely used in modern artificial intelligence projects.
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