中文版 pytorch
| Topic | Replies | Views | Activity | |
|---|---|---|---|---|
|
About the pytorch category
|
|
0 | 1485 | January 14, 2021 |
|
数据操作
|
|
70 | 64240 | February 6, 2026 |
|
线性回归
|
|
92 | 52154 | February 6, 2026 |
|
线性回归的从零开始实现
|
|
159 | 69465 | February 2, 2026 |
|
前言
|
|
23 | 34029 | January 30, 2026 |
|
自注意力和位置编码
|
|
25 | 8257 | January 29, 2026 |
|
注意力汇聚：Nadaraya-Watson 核回归
|
|
54 | 18856 | January 28, 2026 |
|
汇聚层
|
|
29 | 10442 | January 24, 2026 |
|
关于可能的报错
|
|
0 | 120 | January 24, 2026 |
|
图像分类数据集
|
|
72 | 27441 | January 22, 2026 |
|
语言模型和数据集
|
|
39 | 15007 | January 20, 2026 |
|
序列模型
|
|
37 | 13693 | January 18, 2026 |
|
层和块
|
|
46 | 17069 | January 17, 2026 |
|
数据预处理
|
|
187 | 67486 | December 31, 2025 |
|
自动求导
|
|
91 | 49917 | December 30, 2025 |
|
模型选择、欠拟合和过拟合
|
|
86 | 25823 | December 15, 2025 |
|
锚框
|
|
63 | 19166 | December 13, 2025 |
|
为什么在 d2l 的 torch 包中没有 train_ch3 这个函数？
|
|
6 | 2532 | December 8, 2025 |
|
Softmax回归的简洁实现
|
|
120 | 43490 | December 7, 2025 |
|
Softmax回归的从零实现
|
|
155 | 56027 | December 5, 2025 |
|
多层感知机
|
|
34 | 21765 | December 3, 2025 |
|
目标检测和边界框
|
|
14 | 7366 | December 3, 2025 |
|
卷积神经网络（LeNet）
|
|
102 | 41630 | December 2, 2025 |
|
数值稳定性和模型初始化
|
|
17 | 9665 | December 2, 2025 |
|
参数管理
|
|
26 | 15723 | November 30, 2025 |
|
风格迁移
|
|
11 | 5069 | November 27, 2025 |
|
线性代数
|
|
88 | 45979 | July 17, 2025 |
|
实战 Kaggle 比赛：预测房价
|
|
125 | 49389 | November 18, 2025 |
|
Transformer
|
|
52 | 25010 | November 17, 2025 |
|
含并行连结的网络（GoogLeNet）
|
|
28 | 9722 | November 13, 2025 |