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• Model Uncertainty: Model uncertainty refers to the lack of knowledge or confidence in the accuracy of a statistical or machine learning model's predictions. It arises due to various factors such as limited data, noise in the data, model complexity, and assump ... Read More >>
• Photogrammetry: Photogrammetry is the science of making measurements from photographs. In the context of data science and artificial intelligence, photogrammetry is used to extract 3D information from 2D images. This is achieved by analyzing the geometry a ... Read More >>
• Fairness: Fairness in data science refers to the absence of bias or discrimination in the data, algorithms, and models used in decision-making processes. It is important to ensure that the data used to train models is representative of the population ... Read More >>