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AI HyperParameters (“cheatsheet”)
some hyperparameters are specific to certain models or algorithms. Hyperparameters are crucial configurations set before training machine learning models, influencing their performance. Unlike model parameters learned during training, hyperparameters, such as learning rate, batch size, number of epochs, model architecture, activation functions, regularization techniques, and optimizer choice, must be manually set. Proper hyperparameter tuning can…