#CurrencyPairPrediction Techniques to Improve Deep Learning Models for Forex • Regularization: Dropout layers, L1/L2 penalties to prevent overfitting. • Hyperparameter tuning: Adjust learning rate, number of layers, units per layer. • Feature engineering: Provide meaningful technical/fundamental features. • Data augmentation: Include different timeframes, currencies, synthetic samples. • Transfer Learning: Pretrain a model on a general currency dataset, fine-tune it for a specific pair like USD/JPY.