| Topic | Replies | Views | Activity | |
|---|---|---|---|---|
| 微分 |
|
29 | 12782 | December 27, 2025 |
| 语言模型和数据集 |
|
38 | 14355 | December 24, 2025 |
| Gaussian Process Inference |
|
3 | 1640 | December 23, 2025 |
| Multilayer Perceptrons |
|
14 | 7006 | December 16, 2025 |
| The Dataset for Pretraining BERT |
|
7 | 2939 | December 16, 2025 |
| 模型选择、欠拟合和过拟合 |
|
86 | 25152 | December 15, 2025 |
| 汇聚层 |
|
28 | 10091 | December 15, 2025 |
| 锚框 |
|
63 | 18852 | December 13, 2025 |
| 束搜索 |
|
21 | 8742 | December 12, 2025 |
| 为什么在 d2l 的 torch 包中没有 train_ch3 这个函数？ |
|
6 | 2278 | December 8, 2025 |
| Softmax回归的简洁实现 |
|
120 | 42585 | December 7, 2025 |
| Softmax回归的从零实现 |
|
155 | 54974 | December 5, 2025 |
| 从全连接层到卷积 |
|
42 | 19313 | December 4, 2025 |
| 多层感知机 |
|
34 | 21309 | December 3, 2025 |
| 目标检测和边界框 |
|
14 | 7187 | December 3, 2025 |
| 卷积神经网络（LeNet） |
|
102 | 40843 | December 2, 2025 |
| 数值稳定性和模型初始化 |
|
17 | 9461 | December 2, 2025 |
| 参数管理 |
|
26 | 15436 | November 30, 2025 |
| 数据预处理 |
|
186 | 65791 | November 28, 2025 |
| Softmax回归 |
|
78 | 52365 | November 28, 2025 |
| 风格迁移 |
|
11 | 4891 | November 27, 2025 |
| 线性代数 |
|
88 | 44948 | July 17, 2025 |
| Language Models |
|
16 | 5050 | August 6, 2024 |
| Object-Oriented Design for Implementation |
|
15 | 4882 | November 25, 2025 |
| Preface |
|
25 | 10801 | November 22, 2025 |
| 概率 |
|
15 | 5497 | November 21, 2025 |
| 引言 |
|
48 | 41798 | November 21, 2025 |
| 实战 Kaggle 比赛：预测房价 |
|
125 | 48261 | November 18, 2025 |
| Transformer |
|
52 | 24446 | November 17, 2025 |
| 安装 |
|
58 | 46594 | November 16, 2025 |