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
github: https://github.com/pandalabme/d2l/tree/main/exercises 1. If we use an RNN to predict the next character in a text sequence, what is the requir
github: https://github.com/pandalabme/d2l/tree/main/exercises 1. Suppose there are 100,000 words in the training dataset. How much word frequency and
github: https://github.com/pandalabme/d2l/tree/main/exercises import sys import torch.nn as nn import torch import warnings import re import numpy as
问题描述 jupyer lab界面保存文件时提示Jupyter Lab throwing 413: Request Entity Too Large 解决方法 修改nginx配置，在配置中增加/修改client_max_body_size ：
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
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
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
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
github: https://github.com/pandalabme/d2l/tree/main/exercises 1. Should we remove the bias parameter from the fully connected layer or the convolution
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
