Tutorial_06_Transfer_Learning

Transfer Learning Tutorials

This repository contains two tutorials on transfer learning, focusing on TensorFlow and PyTorch frameworks.

Tutorial 1: Transfer Learning with TensorFlow

File: Tutorial#6 (tf) Transfer_learning.ipynb

This tutorial demonstrates transfer learning using TensorFlow. Key highlights include:

• Leveraging pre-trained models from TensorFlow Hub.
• Fine-tuning specific layers to adapt to a custom dataset.
• Practical guidance on optimizing training parameters.

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Tutorial 2: Transfer Learning with PyTorch

File: Tutorial#6 (torch) Transfer_learning.ipynb

This tutorial illustrates transfer learning in PyTorch. Key features covered:

• Using models from torchvision.models with pre-trained weights.
• Freezing layers for efficient training on smaller datasets.
• Step-by-step implementation for model adaptation.

Acknowledgments

• François Chollet
• Tensorflow.org
• pytorch.org