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12 Atomic Experiments in Deep Learning [Notebook]

Deep learning remains somewhat of a mysterious art even for frequent practitioners, because we usually run complex experiments on large datasets, which obscures basic relationships between dataset, hyperparameters, and performance. The goal of this notebook is to provide some basic intuition of deep neural networks by running very simple experiments on small datasets that help understand trends that occur generally on larger datasets.



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12 Atomic Experiments in Deep Learning [Notebook]

https://abidlabs.github.io/Atomic-Experiments

Deep learning remains somewhat of a mysterious art even for frequent practitioners, because we usually run complex experiments on large datasets, which obscures basic relationships between dataset, hyperparameters, and performance. The goal of this notebook is to provide some basic intuition of deep neural networks by running very simple experiments on small datasets that help understand trends that occur generally on larger datasets.



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https://abidlabs.github.io/Atomic-Experiments

12 Atomic Experiments in Deep Learning [Notebook]

Deep learning remains somewhat of a mysterious art even for frequent practitioners, because we usually run complex experiments on large datasets, which obscures basic relationships between dataset, hyperparameters, and performance. The goal of this notebook is to provide some basic intuition of deep neural networks by running very simple experiments on small datasets that help understand trends that occur generally on larger datasets.

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