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Different Perspective of Line Regression
Machine Learning #machine learning

Different Perspective of Line Regression

1. Line regression 1.1 Ordinary Least Squares (OLS) Perspective 1.1.1 Model Representation: The linear regression model is represented as: \hat{Y} = X

narcissuskid narcissuskid 发布于 2024-03-18

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#machine learning 1 #solutions 68 #d2l 68 #pytorch 68 #异常解决 7 #analysis 3 #risk management 1 #vps 6 #羊毛 3
9.1. Working with Sequences
Deep Learning #solutions#d2l#pytorch

9.1. Working with Sequences

github: https://github.com/pandalabme/d2l/tree/main/exercises import sys import torch.nn as nn import torch import warnings sys.path.append('/home/jov

narcissuskid narcissuskid 发布于 2023-09-02
8.8. Designing Convolution Network Architectures
Deep Learning #solutions#d2l#pytorch

8.8. Designing Convolution Network Architectures

github: https://github.com/pandalabme/d2l/tree/main/exercises 1. Increase the number of stages to four. Can you design a deeper RegNetX that performs

narcissuskid narcissuskid 发布于 2023-09-01
8.7. Densely Connected Networks (DenseNet)
Deep Learning #solutions#d2l#pytorch

8.7. Densely Connected Networks (DenseNet)

github: https://github.com/pandalabme/d2l/tree/main/exercises import torch import torch.nn as nn from torch.nn import functional as F import sys sys.p

narcissuskid narcissuskid 发布于 2023-09-01
8.6. Residual Networks (ResNet) and ResNeXt
Deep Learning #solutions#d2l#pytorch

8.6. Residual Networks (ResNet) and ResNeXt

github: https://github.com/pandalabme/d2l/tree/main/exercises 1. What are the major differences between the Inception block in Fig. 8.4.1 and the resi

narcissuskid narcissuskid 发布于 2023-08-31
8.5. Batch Normalization
Deep Learning #solutions#d2l#pytorch

8.5. Batch Normalization

github: https://github.com/pandalabme/d2l/tree/main/exercises 1. Should we remove the bias parameter from the fully connected layer or the convolution

narcissuskid narcissuskid 发布于 2023-08-30
8.4. Multi-Branch Networks (GoogLeNet)
Deep Learning #solutions#d2l#pytorch

8.4. Multi-Branch Networks (GoogLeNet)

github: https://github.com/pandalabme/d2l/tree/main/exercises import sys import torch.nn as nn import torch import warnings sys.path.append('/home/jov

narcissuskid narcissuskid 发布于 2023-08-28
8.3. Network in Network (NiN)
Deep Learning #solutions#d2l#pytorch

8.3. Network in Network (NiN)

github: https://github.com/pandalabme/d2l/tree/main/exercises import sys import torch.nn as nn import torch import warnings sys.path.append('/home/jov

narcissuskid narcissuskid 发布于 2023-08-27
8.2. Networks Using Blocks (VGG)
Deep Learning #solutions#d2l#pytorch

8.2. Networks Using Blocks (VGG)

github: https://github.com/pandalabme/d2l/tree/main/exercises import sys import torch.nn as nn import torch import warnings sys.path.append('/home/jov

narcissuskid narcissuskid 发布于 2023-08-27
8.1. Deep Convolutional Neural Networks (AlexNet)
Deep Learning #solutions#d2l#pytorch

8.1. Deep Convolutional Neural Networks (AlexNet)

github: https://github.com/pandalabme/d2l/tree/main/exercises import sys import torch.nn as nn import torch import warnings sys.path.append('/home/jov

narcissuskid narcissuskid 发布于 2023-08-27
7.6. Convolutional Neural Networks (LeNet)
Deep Learning #solutions#d2l#pytorch

7.6. Convolutional Neural Networks (LeNet)

github: https://github.com/pandalabme/d2l/tree/main/exercises import sys import torch.nn as nn import torch import warnings sys.path.append('/home/jov

narcissuskid narcissuskid 发布于 2023-08-26
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