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* [ 4. Quantifying CNN spatial priors] ( https://github.com/greydanus/mnist1d/blob/master/notebooks/mnist1d-classification.ipynb ) ([ Colab] ( https://githubtocolab.com/greydanus/mnist1d/blob/master/notebooks/mnist1d-classification.ipynb ) )
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* [ 5. Self-supervised learning] ( https://github.com/greydanus/mnist1d/blob/master/notebooks/self-supervised-learning.ipynb ) ([ Colab] ( https://githubtocolab.com/greydanus/mnist1d/blob/master/notebooks/self-supervised-learning.ipynb ) )
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* [ 6. Finding lottery tickets] ( https://github.com/greydanus/mnist1d/blob/master/notebooks/lottery-tickets.ipynb ) ([ Colab] ( https://githubtocolab.com/greydanus/mnist1d/blob/master/notebooks/lottery-tickets.ipynb ) )
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- * [ 7. Observing deep double descent] ( https://github.com/greydanus/mnist1d/blob/master/notebooks/deep-double_descent .ipynb ) ([ Colab] ( https://githubtocolab.com/greydanus/mnist1d/blob/master/notebooks/deep-double-descent.ipynb ) )
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+ * [ 7. Observing deep double descent] ( https://github.com/greydanus/mnist1d/blob/master/notebooks/deep-double-descent .ipynb ) ([ Colab] ( https://githubtocolab.com/greydanus/mnist1d/blob/master/notebooks/deep-double-descent.ipynb ) )
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* [ 8. Metalearning a learning rate] ( https://github.com/greydanus/mnist1d/blob/master/notebooks/metalearn-learn-rate.ipynb ) ([ Colab] ( https://githubtocolab.com/greydanus/mnist1d/blob/master/notebooks/metalearn-learn-rate.ipynb ) )
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* [ 9. Metalearning an activation function] ( https://github.com/greydanus/mnist1d/blob/master/notebooks/metalearn-activation-function.ipynb ) ([ Colab] ( https://githubtocolab.com/greydanus/mnist1d/blob/master/notebooks/metalearn-activation-function.ipynb ) )
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* [ 10. Benchmarking pooling methods] ( https://github.com/greydanus/mnist1d/blob/master/notebooks/benchmark-pooling.ipynb ) ([ Colab] ( https://githubtocolab.com/greydanus/mnist1d/blob/master/notebooks/benchmark-pooling.ipynb ) )
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