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📚 Boosting Classification Accuracy: Integrating Transfer Learning and Data Augmentation for Enhanced Machine Learning Performance


Nachrichtenbereich: 🔧 AI Nachrichten
🔗 Quelle: marktechpost.com

Transfer learning is particularly beneficial when there is a distribution shift between the source and target datasets and a scarcity of labeled samples in the target dataset. By leveraging knowledge from a related source domain, a pre-trained model can capture general relevant patterns and features to both domains, allowing the model to adapt more effectively […]

The post Boosting Classification Accuracy: Integrating Transfer Learning and Data Augmentation for Enhanced Machine Learning Performance appeared first on MarkTechPost.

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