What is transfer learning, and how is it implemented in Python AI?

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Aliva

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In Python for AI, transfer learning is a technique where a pre-trained model is reused for a new but related task, saving time and data. Python for AI projects often fine-tune models like VGG, ResNet, or BERT using TensorFlow or PyTorch. You load the base model, freeze initial layers to retain learned features, and retrain the top layers on your dataset, improving accuracy and efficiency for tasks like image or text classification.

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Topic starter Posted : 12/08/2025 12:45 pm

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