Data architecture is a set of rules, policies, standards, and models that govern and determine the type of data collected, and show how this data is used, stored, managed, and integrated within an enterprise and database systems. It offers a formal approach to creating and managing data flow and how data is processed across an enterprise's IT systems and applications.
Transfer Learning is a powerful technique used to speed up the training process and improve the performance of artificial intelligence and machine learning models. Transfer learning enables a model to reuse knowledge learned in a previous task in another task.
In AI and machine learning projects, instead of processing raw data directly, it is necessary to make it more meaningful and processable. An important concept that comes into play at this point is Embedding.
Demand forecasts help make the right business decisions by predicting future demands for products and services. Demand forecasts cover finely detailed data, historical sales data, surveys and more.
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