5.1. Multilayer Perceptrons

github: https://github.com/pandalabme/d2l/tree/main/exercises 1. Show that adding layers to a linear deep network, i.e., a network without nonlinearit

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4.7. Environment and Distribution Shift

github: https://github.com/pandalabme/d2l/tree/main/exercises 1. What could happen when we change the behavior of a search engine? What might the user

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4.6. Generalization in Classification

github: https://github.com/pandalabme/d2l/tree/main/exercises 1. If we wish to estimate the error of a fixed model f to within 0.0001 with probability

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4.5. Concise Implementation of Softmax Regression

github: https://github.com/pandalabme/d2l/tree/main/exercises

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4.4. Softmax Regression Implementation from Scratch

github: https://github.com/pandalabme/d2l/tree/main/exercises import torch import warnings import matplotlib.pyplot as plt import sys sys.path.append(

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4.3. The Base Classification Model

github: https://github.com/pandalabme/d2l/tree/main/exercises 1. Denote by L_v the validation loss, and let

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4.2. The Image Classification Dataset

github: https://github.com/pandalabme/d2l/tree/main/exercises 1. Does reducing the batch_size (for instance, to 1) affect the reading performance? Red

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4.1 Softmax Regression

github: https://github.com/pandalabme/d2l/tree/main/exercises 1. We can explore the connection between exponential families and softmax in some more d

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3.7. Weight Decay

github: https://github.com/pandalabme/d2l/tree/main/exercises 1. Experiment with the value of \lambda in the estimation problem in this section. Plot

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3.6. Generalization

github: https://github.com/pandalabme/d2l/tree/main/exercises 1. When can you solve the problem of polynomial regression exactly? Polynomial regressio

narcissuskid narcissuskid 发布于 2023-08-16