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• file:CVPR2020Papers.zip
• file:人工智能大纲升级版本.pdf
• file:论文集索引.jpg
• file:9. 8-论文总结分析.mp4
• file:8. 7-BERT模型训练策略.mp4
• file:7. 6-向量特征编码方法.mp4
• file:6. 5-输入数据特殊编码字符解析.mp4
• file:5. 4-预训练模型的作用.mp4
• file:4. 3-模型在NLP领域应用效果.mp4
• file:1. 课程介绍.mp4
• file:13-额外补充-Resnet论文解读.mp4
• file:ICCV-2.zip
• file:5. 4-基于图卷积构建人体拓扑关系.mp4
• file:1. 1-关键点位置特征构建.mp4
• file:Szegedy_Going_Deeper_With_2015_CVPR_paper.pdf
• file:4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf
• file:1512.03385v1_Deep Residual Learning for Image Recognition.pdf
• file:1506.02025_Spatial Transformer Networks.pdf
• file:1506.01497v3_Faster R-CNN.pdf
• file:1412.2306v2_Deep Visual-Semantic Alignments for Generating Image Descriptions.pdf
• file:1409.1556v6_VERY DEEP CONVOLUTIONAL Networks.pdf
• file:1406.2661v1_Generative Adversarial Nets.pdf
• file:1311.2901v3_Visualizing and Understanding Convolutional Networks.pdf
• file:1311.2524v5_R_CNN.pdf
• file:Deep-Learning-with-PyTorch-Tutorials.zip
• file:9. 课时9 LSTM中Layer的使用.mp4
• file:6. 课时6 项目实战-时间序列预测问题.mp4
• file:3. 课时3 循环神经网络基本原理-2.mp4
• file:10. 课时10 RNN训练难题—梯度弥散与梯度爆炸.mp4
• file:9 GAN实战-1.flv
• file:7 EM距离.flv
• file:3 生成对抗网络.flv
• file:2 画家的成长历程.flv