"Element: SGD, Adam, RProp, L-BFGS Komponén: Gradients, Weights, Biases Fungsi: Parameter update, Modél pamutahiran Kualitas: Online, Batch, Mini-batch Data Pra-processing: Elemen: Normalization, Standardization, Coding, Imputation Komponén: Mean, Standard deviation, One-hot coding, Imputation Strategy Fungsi: Data cleaning, Data preparation Kualitas: Numerical, Pyorical, Ordinal Evaluation Metrics: Elements: Accuracy, Precision, Recall, F1-Score, ROC-AUC Komponén: Confusion matrix, True positive, True negative Trainable, True negative Functions: Model Performance Trainable Trainable: Qualities: Binary attention, Multi-Py-C
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