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Fundamentals of Deep Learning

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Section 7: Notebook - train vs validation sets (Fundamentals of Deep Learning)

Jan 20, 2021 · Professor Parr

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Section 8: Notebook - binary classification (Fundamentals of Deep Learning)

Jan 19, 2021 · Professor Parr

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Section 9: Notebook - k-class classification (Fundamentals of Deep Learning)

Jan 19, 2021 · Professor Parr

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Section 10: Notebook - training with a GPU (Fundamentals of Deep Learning)

Jan 19, 2021 · Professor Parr

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Section 11: Notebook - stochastic gradient descent (Fundamentals of Deep Learning)

Jan 19, 2021 · Professor Parr

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Section 12: Notebook - PyTorch DataLoaders (Fundamentals of Deep Learning)

Jan 19, 2021 · Professor Parr

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Section 6: Notebook - PyTorch regression (Fundamentals of Deep Learning)

Jan 19, 2021 · Professor Parr

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Section 5: Notebook - Intro to regression (Fundamentals of Deep Learning)

Jan 18, 2021 · Professor Parr

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Section 2: Deep learning regressors (Fundamentals of Deep Learning)

Jan 18, 2021 · Professor Parr

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Section 4: Training deep learning models (Fundamentals of Deep Learning)

Jan 18, 2021 · Professor Parr

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