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.
Pre-training refers to pre-training a model on large data sets and then fine-tuning it to perform a specific task. This technique is widely used, especially in areas such as natural language processing (NLP) and image processing.
Supply chain management refers to the optimization of the flow from the supply of raw materials of a product to its production, from the logistics process to its delivery to the final customer.
Automated machine learning, called AutoML (Automated Machine Learning) in the field of artificial intelligence and machine learning, describes integrated software platforms for the creation, training and optimization of a machine learning model.
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