李宏毅老师深度学习PPT

上传者: 32599109 | 上传时间: 2022-08-20 10:33:37 | 文件大小: 670.84MB | 文件类型: ZIP
深度学习课程全套PPT设计各种新技术如元学习,life long learning,强化学习等,适合仔细学习研究。

文件下载

资源详情

[{"title":"( 57 个子文件 670.84MB ) 李宏毅老师深度学习PPT","children":[{"title":"PPT","children":[{"title":"Unsupervised Learning-Deep Generation model.pptx <span style='color:#111;'> 22.35MB </span>","children":null,"spread":false},{"title":"GAN_8.pptx <span style='color:#111;'> 35.63MB </span>","children":null,"spread":false},{"title":"GAN_2.pptx <span style='color:#111;'> 10.11MB </span>","children":null,"spread":false},{"title":"Logistic Regression (v4).pptx <span style='color:#111;'> 1.67MB </span>","children":null,"spread":false},{"title":"Research trends of deep reinforcement learning.pdf <span style='color:#111;'> 4.61MB </span>","children":null,"spread":false},{"title":"SeqToSeq1.pdf <span style='color:#111;'> 2.79MB </span>","children":null,"spread":false},{"title":"RL Advanced_Proximal Policy Optimization.pptx <span style='color:#111;'> 31.72MB </span>","children":null,"spread":false},{"title":"BERT (v3).pptx <span style='color:#111;'> 7.50MB </span>","children":null,"spread":false},{"title":"GAN_6.pptx <span style='color:#111;'> 74.65MB </span>","children":null,"spread":false},{"title":"GNN.pdf <span style='color:#111;'> 30.62MB </span>","children":null,"spread":false},{"title":"GAN.pdf <span style='color:#111;'> 4.70MB </span>","children":null,"spread":false},{"title":"Meta_learning_and_more.pdf <span style='color:#111;'> 52.54MB </span>","children":null,"spread":false},{"title":"Regression.pptx <span style='color:#111;'> 2.56MB </span>","children":null,"spread":false},{"title":"Meta Learning_1.pptx <span style='color:#111;'> 3.34MB </span>","children":null,"spread":false},{"title":"Lifelong Learning (v9).pptx <span style='color:#111;'> 2.58MB </span>","children":null,"spread":false},{"title":"GAN _1(v2).pptx <span style='color:#111;'> 5.83MB </span>","children":null,"spread":false},{"title":"Backpropagation.pptx <span style='color:#111;'> 522.94KB </span>","children":null,"spread":false},{"title":"GAN_3.pptx <span style='color:#111;'> 5.70MB </span>","children":null,"spread":false},{"title":"Unsupervised Learning-Word Embedding.pdf <span style='color:#111;'> 1.39MB </span>","children":null,"spread":false},{"title":"Adversarial Attack.pdf <span style='color:#111;'> 1.96MB </span>","children":null,"spread":false},{"title":"Attack (v8).pptx <span style='color:#111;'> 31.00MB </span>","children":null,"spread":false},{"title":"GAN_5.pptx <span style='color:#111;'> 1.67MB </span>","children":null,"spread":false},{"title":"Anomaly Detection.pdf <span style='color:#111;'> 2.35MB </span>","children":null,"spread":false},{"title":"Anomaly Detection (v9) (1).pptx <span style='color:#111;'> 55.21MB </span>","children":null,"spread":false},{"title":"MoreLL.pdf <span style='color:#111;'> 2.40MB </span>","children":null,"spread":false},{"title":"GAN_10.pptx <span style='color:#111;'> 1.53MB </span>","children":null,"spread":false},{"title":"CNN.pptx <span style='color:#111;'> 5.35MB </span>","children":null,"spread":false},{"title":"RL Advanced_Sparse Reward.pptx <span style='color:#111;'> 30.54MB </span>","children":null,"spread":false},{"title":"Unsupervised Learning-Neighbor Embedding.pptx <span style='color:#111;'> 2.38MB </span>","children":null,"spread":false},{"title":"Unsupervised Learning-Linear Methods.pptx <span style='color:#111;'> 4.37MB </span>","children":null,"spread":false},{"title":"GAN_4.pptx <span style='color:#111;'> 2.19MB </span>","children":null,"spread":false},{"title":"Explainable AI.pdf <span style='color:#111;'> 5.58MB </span>","children":null,"spread":false},{"title":"GAN_9.pptx <span style='color:#111;'> 6.89MB </span>","children":null,"spread":false},{"title":"Meta Learning_2.pptx <span style='color:#111;'> 3.76MB </span>","children":null,"spread":false},{"title":"Network Compression.pptx <span style='color:#111;'> 3.76MB </span>","children":null,"spread":false},{"title":"Explainable ML.pptx <span style='color:#111;'> 10.12MB </span>","children":null,"spread":false},{"title":"RL Advanced_Actor-Critic.pdf <span style='color:#111;'> 798.13KB </span>","children":null,"spread":false},{"title":"RL Advanced_QLearning (v2).pptx <span style='color:#111;'> 34.78MB </span>","children":null,"spread":false},{"title":"Optimization.pdf <span style='color:#111;'> 2.55MB </span>","children":null,"spread":false},{"title":"semi-supervised.pptx <span style='color:#111;'> 1.51MB </span>","children":null,"spread":false},{"title":"SeqToSeq2.pdf <span style='color:#111;'> 738.21KB </span>","children":null,"spread":false},{"title":"TransferLearning.pptx <span style='color:#111;'> 6.75MB </span>","children":null,"spread":false},{"title":"Deep Reinforcemen Learning.pptx <span style='color:#111;'> 5.38MB </span>","children":null,"spread":false},{"title":"Self-Supervised Learning.pdf <span style='color:#111;'> 3.22MB </span>","children":null,"spread":false},{"title":"Basic Concept.pptx <span style='color:#111;'> 1.17MB </span>","children":null,"spread":false},{"title":"Classification (v2).pptx <span style='color:#111;'> 2.04MB </span>","children":null,"spread":false},{"title":"New Architecture.pdf <span style='color:#111;'> 3.98MB </span>","children":null,"spread":false},{"title":"RNN.pptx <span style='color:#111;'> 5.98MB </span>","children":null,"spread":false},{"title":"More about Auto-Encoder.pptx <span style='color:#111;'> 6.23MB </span>","children":null,"spread":false},{"title":"ML 108-2 Domain Adaptation.pdf <span style='color:#111;'> 65.28MB </span>","children":null,"spread":false},{"title":"Brief Introduction of DeepLearning.pptx <span style='color:#111;'> 1.69MB </span>","children":null,"spread":false},{"title":"Unsupervised Learning-Auto-encoder.pptx <span style='color:#111;'> 2.70MB </span>","children":null,"spread":false},{"title":"RL Advanced_Imitation Learning.pptx <span style='color:#111;'> 64.75MB </span>","children":null,"spread":false},{"title":"GAN_7.pptx <span style='color:#111;'> 1.28MB </span>","children":null,"spread":false},{"title":"Gradient Descent.pptx <span style='color:#111;'> 1.65MB </span>","children":null,"spread":false},{"title":"Tips for Training DNN.pptx <span style='color:#111;'> 2.14MB </span>","children":null,"spread":false},{"title":"Transformer (v5).pptx <span style='color:#111;'> 12.99MB </span>","children":null,"spread":false}],"spread":false}],"spread":true}]

评论信息

免责申明

【只为小站】的资源来自网友分享,仅供学习研究,请务必在下载后24小时内给予删除,不得用于其他任何用途,否则后果自负。基于互联网的特殊性,【只为小站】 无法对用户传输的作品、信息、内容的权属或合法性、合规性、真实性、科学性、完整权、有效性等进行实质审查;无论 【只为小站】 经营者是否已进行审查,用户均应自行承担因其传输的作品、信息、内容而可能或已经产生的侵权或权属纠纷等法律责任。
本站所有资源不代表本站的观点或立场,基于网友分享,根据中国法律《信息网络传播权保护条例》第二十二条之规定,若资源存在侵权或相关问题请联系本站客服人员,zhiweidada#qq.com,请把#换成@,本站将给予最大的支持与配合,做到及时反馈和处理。关于更多版权及免责申明参见 版权及免责申明