ML ZOOMCAMP 2025 - Module 8

 Module 8: Neural networks and Deep learning

In module we learned how to build an image classification model using PyTorch and transfer learning. We used a clothing dataset.

What was covered

  • Introduction to PyTorch for deep learning
  • Loading and preprocessing image data
  • Using pre-trained models (MobileNetV2)
  • Understanding convolutional neural networks (CNNs)
  • Transfer learning: adapting pre-trained models
  • Hyperparameter tuning: learning rate optimization
  • Model checkpointing: saving the best model
  • Adding more layers to improve performance
  • Dropout regularization to prevent overfitting
  • Data augmentation for better generalization
  • Training the final model
  • Using the model for predictions
  • Exporting models to ONNX format




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