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深度学习 李宏毅 2021 学习笔记
| Date | Stars |
|---|---|
| 2026-07-31 | 1658 |
| 2026-08-01 | 1660 |
| 2026-08-06 | 1661 |
Today
+1 stars today
This week
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## HTML 链接 [01_Regression_P1](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/01_Regression_P1.pdf) [02_Regression_P2](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/02_Regression_P2.pdf) [03_GeneralGuidance_Overfitting](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/03_General%20Guidance.pdf) [04_Local Minimum And Saddle Point](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/04_Local%20Minimum%20And%20Saddle%20Point.pdf) [05_Batch and Momentum](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/05_Batch%20and%20Momentum.pdf) [06_Adaptive Learning Rate](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/06_Adaptive%20Learning%20Rate.pdf) [07_Batch Normalization](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/07_Batch%20Normalization.pdf) [08_Classification](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/08_Classification.pdf) [09_CNN](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/09_CNN.pdf) [10_Self-Attention P1](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/10_Self-attention_P1.pdf) [11_Self-Attention P2](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/11_Self-attention_P2.pdf) [12_Transformer P1](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/12_Transformer_P1.pdf) [13_Transformer P2](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/13_Transformer_P2.pdf) [14_GAN P1](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/14_GAN_P1.pdf) [15_GAN P2](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/15_GAN_P2.pdf) [16_GAN P3](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/16_GAN_P3.pdf) [17_GAN P4](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/17_GAN_P4.pdf) [18_BERT_P1](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/18_BERT_P1.pdf) [19_BERT_P2](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/19_BERT_P2.pdf) [20_BERT_P3](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/20_BERT_P3.pdf) [21_Auto-encoder_P1](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/21_Auto-encoder_P1.pdf) [22_Auto-encoder_P2](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/22_Auto-encoder_P2.pdf) [23_Adversarial Attack_P1](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/23_Adversarial%20Attack_P1.pdf) [24_Adversarial Attack_P2](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/24_Adversarial%20Attack_P2.pdf) [25_Explainable AI_P1](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/25_Explainable%20AI_P1.pdf) [26_Explainable AI_P2](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/26_Explainable%20AI_P2.pdf) [27_Domain Adaptation](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/27_Domain%20Adaptation.pdf) [28_Reinforcement Learning_P1](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/28_Reinforcement%20Learning_P1.pdf) [29_Reinforcement Learning_P2](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/29_Reinforcement%20Learning_P2.pdf) [30_Reinforcement Learning_P3](https://github.com/unclestrong/DeepLearning_LHY21_Notes/blob/master/Notes_PDF/30_Reinforcement%20Learning_P3.pdf)
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:b65c4d8cf6bb794f, llm:Repository description: '深度学习 李宏毅 2021 学习笔记' (Deep Learning Li Hongyi 2021 study notes). No topics; HTML language files likely contain lecture notes.