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license: apache-2.0
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Implemented as a **Multi-Layer Perceptron to classify handwritten Digits (0-9)**
[[Annotated Notebook](https://github.com/dcarpintero/fastai-deeplearning/blob/main/course2024/lesson_03.full.mnist.mlp.md)]
**Model Architecture and Results**
The model comprises a flattening layer and three linear layers `((256, 64) hidden dimensions)` with relus to approximate non-linearity. It achieves 95.6% accuracy after `15 training epochs` and `batch size = 64`. Taining and Test MNIST datasets are loaded with PyTorch [dataloaders](https://pytorch.org/tutorials/beginner/basics/data_tutorial.html).
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