Completed
- Data Split Training, Validation, Testing
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Classroom Contents
Training MNIST Perceptron with PyTorch - Lab 3.4
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- 1 - Recap
- 2 - PyTorch Datasets, One-Hot Encoding of Labels
- 3 - Data Split Training, Validation, Testing
- 4 - PyTorch DataLoaders and Mini Batches
- 5 - The Training Loop for a Neural Network
- 6 - Improved Training Loop Loss Data Collection & Validation
- 7 - Running the Training Loop
- 8 - Plotting the Loss Curves
- 9 - Saving and Loading PyTorch Models for Inference
- 10 - Incremental and Full-Batch Updates
