4.3 模型验证【stanford-cs329p】

Jun 6 stanford-cs329p Comments Word Count: 556(words) Read Count: 1(minutes)

4.2 过拟合和欠拟合【stanford-cs329p】

Jun 6 stanford-cs329p Comments Word Count: 562(words) Read Count: 1(minutes)

GTC-2020 Megatron-LM：Training Multi-Billion Parameter Language Models Using Model Parallelism

Jun 4 PaperNote OS Comments Word Count: 848(words) Read Count: 3(minutes)

NIPS-2019 GPipe：Efficient Training of Giant Neural Networks using Pipeline Parallelism

Jun 3 PaperNote OS Comments Word Count: 1.5k(words) Read Count: 5(minutes)

4.1 模型评估【stanford-cs329p】

May 14 stanford-cs329p Comments Word Count: 813(words) Read Count: 2(minutes)

3.7 循环神经网络【stanford-cs329p】

May 13 stanford-cs329p Comments Word Count: 478(words) Read Count: 1(minutes)

EMNLP-2021 Rethinking Data Augmentation for Low-Resource Neural Machine Translation：A Multi-Task Learning Approach

May 12 PaperNote CL Comments Word Count: 849(words) Read Count: 2(minutes)

3.6 卷积神经网络【stanford-cs329p】

May 12 stanford-cs329p Comments Word Count: 560(words) Read Count: 2(minutes)

3.5 多层感知机【stanford-cs329p】

May 12 stanford-cs329p Comments Word Count: 252(words) Read Count: 1(minutes)

3.4 随机梯度下降【stanford-cs329p】

May 12 stanford-cs329p Comments Word Count: 304(words) Read Count: 1(minutes)