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Introduction to Machine Learning with PyTorch

  1. Building simple networks with PyTorch
  2. Tensors and automatic differentiation
  3. Creating and training models
  4. MicroSim: PyTorch model builder
  5. Comparing traditional and deep learning approaches
  6. GPU acceleration and optimization
  7. Model saving and deployment