Data-Driven Models

Data-driven models are models that are built using data as the primary input. These models are designed to learn from the data and make predictions or decisions based on that learning. Data-driven models are used in a variety of fields, including machine learning, artificial intelligence, and data science. These models are often used to analyze large datasets and identify patterns or trends that would be difficult or impossible to detect using traditional statistical methods. Data-driven models can be used for a wide range of applications, including predictive modeling, anomaly detection, and decision-making. These models are typically built using algorithms that are designed to learn from the data and improve their accuracy over time.
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