Deep Learning Projects with PyTorch [Video]
| 文件类型 | 收录时间 | 最后活跃 | 资源热度 | 文件大小 | 文件数量 |
|---|---|---|---|---|---|
| 视频 | 2019-1-4 21:50 | 2024-6-27 03:47 | 79 | 595.12 MB | 27 |
迅雷链接
二维码链接
种子下载(838888不存储任何种子文件)
文件列表
- 1.Getting Ready with PyTorch/02.Using PyTorch.mp438.82MB
- 1.Getting Ready with PyTorch/03.Understanding Regression.mp412.36MB
- 1.Getting Ready with PyTorch/04.Linear Regression and Logistic Regression.mp432.91MB
- 2.Convolutional Neural Network/05.Understanding Convolutional Neural Network.mp417.03MB
- 2.Convolutional Neural Network/06.Looking into Images from a Machine Perspective.mp422.28MB
- 2.Convolutional Neural Network/07.Making CNN.mp432.16MB
- 2.Convolutional Neural Network/08.Pooling Layers.mp418.6MB
- 2.Convolutional Neural Network/09.Output Layer.mp420.52MB
- 3.Understanding RNN and LSTM/10.Understanding Recurrent Neural Network.mp428.01MB
- 3.Understanding RNN and LSTM/11.Making RNN for Prediction.mp429.62MB
- 3.Understanding RNN and LSTM/12.Why LSTM.mp449.66MB
- 3.Understanding RNN and LSTM/13.Moving to LSTM.mp410.14MB
- 4.Using Autoencoders for Fraud Detection/14.Getting Ready with Data.mp425.9MB
- 4.Using Autoencoders for Fraud Detection/15.Developing a Model.mp426.48MB
- 4.Using Autoencoders for Fraud Detection/16.Getting Output.mp48.2MB
- 5.Recommending a Movie with Boltzmann Machines/17.Introduction to Boltzmann Machines.mp439.7MB
- 5.Recommending a Movie with Boltzmann Machines/18.Getting Ready for Recommender System.mp417.66MB
- 5.Recommending a Movie with Boltzmann Machines/19.Making Boltzmann Machines.mp458.07MB
- 5.Recommending a Movie with Boltzmann Machines/20.Getting Output.mp43.87MB
- 6.Movie Rating Using a Autoencoders/21.Introduction to Autoencoders.mp431.22MB
- 6.Movie Rating Using a Autoencoders/22.Getting Ready for Recommender System.mp48MB
- 6.Movie Rating Using a Autoencoders/23.Making Autoencoders.mp422.71MB
- 6.Movie Rating Using a Autoencoders/24.Getting Output.mp43.82MB
- 7.Making Model for Object Recognition/25.Getting Ready with Data.mp47.94MB
- 7.Making Model for Object Recognition/26.Developing a Model.mp415.77MB
- 7.Making Model for Object Recognition/27.Getting Output.mp49.38MB
- 1.Getting Ready with PyTorch/01.The Course Overview.mp44.27MB
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概述
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它通过BitTorrent协议加入DHT网络，实时的自动采集数据，仅存储文件的标题、大小、文件列表、文件标识符（磁力链接）等基础信息
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