👉 Prediction engineering is an approach in machine learning and artificial intelligence that focuses on designing and optimizing models to make accurate predictions by systematically engineering the prediction process. This involves crafting features, selecting appropriate model architectures, and tuning hyperparameters to enhance the model's ability to forecast outcomes effectively. By focusing on prediction quality rather than just model accuracy, prediction engineering aims to improve the robustness, interpretability, and generalization capabilities of models, ultimately leading to better performance in real-world applications. This method often includes techniques such as active learning, where the model actively selects the most informative data points for labeling, and Bayesian optimization, which efficiently searches for optimal hyperparameters.
