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fundamentals deep

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  1. Section 7: Notebook - train vs validation sets (Fundamentals of Deep Learning)Fundamentals of Deep LearningNotes
  2. Section 8: Notebook - binary classification (Fundamentals of Deep Learning)Fundamentals of Deep LearningNotes
  3. Section 9: Notebook - k-class classification (Fundamentals of Deep Learning)Fundamentals of Deep LearningNotes
  4. Section 10: Notebook - training with a GPU (Fundamentals of Deep Learning)Fundamentals of Deep LearningNotes
  5. Section 11: Notebook - stochastic gradient descent (Fundamentals of Deep Learning)Fundamentals of Deep LearningNotes
  6. Section 12: Notebook - PyTorch DataLoaders (Fundamentals of Deep Learning)Fundamentals of Deep LearningNotes
  7. Section 6: Notebook - PyTorch regression (Fundamentals of Deep Learning)Fundamentals of Deep LearningNotes
  8. Section 5: Notebook - Intro to regression (Fundamentals of Deep Learning)Fundamentals of Deep LearningNotes
  9. Section 2: Deep learning regressors (Fundamentals of Deep Learning)Fundamentals of Deep LearningNotes
  10. Section 4: Training deep learning models (Fundamentals of Deep Learning)Fundamentals of Deep LearningNotes

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