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翻译征集
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- 机器学习/数据科学相关
- 或者编程相关
- 原文必须在互联网上开放
- 不能只提供 PDF 格式(我们实在不想把精力都花在排版上)
- 请先搜索有没有人翻译过
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翻译活动
PyTorch 1.0 文档翻译活动
参与方式:https://github.com/apachecn/pytorch-doc-zh/blob/master/CONTRIBUTING.md
整体进度:https://github.com/apachecn/pytorch-doc-zh/issues/274
项目仓库:https://github.com/apachecn/pytorch-doc-zh
进度:教程部分:认领 35/37,翻译 26/37;文档部分:16/39,翻译 8/39
章节 | 贡献者 | 进度 |
教程部分 | - | - |
Deep Learning with PyTorch: A 60 Minute Blitz | @bat67 | 100% |
What is PyTorch? | @bat67 | 100% |
Autograd: Automatic Differentiation | @bat67 | 100% |
Neural Networks | @bat67 | 100% |
Training a Classifier | @bat67 | 100% |
Optional: Data Parallelism | @bat67 | 100% |
Data Loading and Processing Tutorial | @yportne13 | 100% |
Learning PyTorch with Examples | @bat67 | 100% |
Transfer Learning Tutorial | @jiangzhonglian | 100% |
Deploying a Seq2Seq Model with the Hybrid Frontend | @cangyunye | 100% |
Saving and Loading Models | @sfyumi | |
What is <cite>torch.nn</cite> really? | @lhc741 | |
Finetuning Torchvision Models | @ZHHAYO | 100% |
Spatial Transformer Networks Tutorial | @PEGASUS1993 | 100% |
Neural Transfer Using PyTorch | @bdqfork | 100% |
Adversarial Example Generation | @cangyunye | 100% |
Transfering a Model from PyTorch to Caffe2 and Mobile using ONNX | @PEGASUS1993 | 100% |
Chatbot Tutorial | @a625687551 | 100% |
Generating Names with a Character-Level RNN | @hhxx2015 | 100% |
Classifying Names with a Character-Level RNN | @hhxx2015 | 100% |
Deep Learning for NLP with Pytorch | @BreezeHavana | |
Introduction to PyTorch | @guobaoyo | 100% |
Deep Learning with PyTorch | @bdqfork | 100% |
Word Embeddings: Encoding Lexical Semantics | @sight007 | |
Sequence Models and Long-Short Term Memory Networks | @ETCartman | 100% |
Advanced: Making Dynamic Decisions and the Bi-LSTM CRF | @JohnJiangLA | |
Translation with a Sequence to Sequence Network and Attention | @mengfu188 | 100% |
DCGAN Tutorial | @wangshuai9517 | |
Reinforcement Learning (DQN) Tutorial | @BreezeHavana | |
Creating Extensions Using numpy and scipy | ||
Custom C++ and CUDA Extensions | @Lotayou | |
Extending TorchScript with Custom C++ Operators | ||
Writing Distributed Applications with PyTorch | @firdameng | |
PyTorch 1.0 Distributed Trainer with Amazon AWS | @yportne13 | 100% |
ONNX Live Tutorial | @PEGASUS1993 | 100% |
Loading a PyTorch Model in C++ | @talengu | 100% |
Using the PyTorch C++ Frontend | @solerji | 100% |
文档部分 | - | - |
Autograd mechanics | @PEGASUS1993 | 100% |
Broadcasting semantics | @PEGASUS1993 | 100% |
CUDA semantics | @jiangzhonglian | 100% |
Extending PyTorch | @PEGASUS1993 | |
Frequently Asked Questions | @PEGASUS1993 | |
Multiprocessing best practices | @cvley | |
Reproducibility | @WyattHuang1 | |
Serialization semantics | ||
Windows FAQ | @PEGASUS1993 | |
torch | ||
torch.Tensor | @hijkzzz | 100% |
Tensor Attributes | ||
Type Info | @PEGASUS1993 | 100% |
torch.sparse | ||
torch.cuda | @bdqfork | 100% |
torch.Storage | ||
torch.nn | ||
torch.nn.functional | @hijkzzz | |
torch.nn.init | @GeneZC | |
torch.optim | @qiaokuoyuan | |
Automatic differentiation package - torch.autograd | ||
Distributed communication package - torch.distributed | ||
Probability distributions - torch.distributions | ||
Torch Script | ||
Multiprocessing package - torch.multiprocessing | @hijkzzz | 100% |
torch.utils.bottleneck | ||
torch.utils.checkpoint | ||
torch.utils.cpp_extension | ||
torch.utils.data | ||
torch.utils.dlpack | ||
torch.hub | ||
torch.utils.model_zoo | ||
torch.onnx | @guobaoyo | 100% |
Distributed communication package (deprecated) - torch.distributed.deprecated | ||
torchvision Reference | ||
torchvision.datasets | ||
torchvision.models | ||
torchvision.transforms | ||
torchvision.utils |
HBase 参考指南 3.0 翻译活动
参与方式:https://github.com/apachecn/hbase-doc-zh/blob/master/CONTRIBUTING.md
整体进度:https://github.com/apachecn/hbase-doc-zh/issues/1
项目仓库:https://github.com/apachecn/hbase-doc-zh
进度:认领 1/31,翻译 0/31
章节 | 译者 | 进度 |
Preface | ||
Getting Started | ||
Apache HBase Configuration | ||
Upgrading | ||
The Apache HBase Shell | ||
Data Model | ||
HBase and Schema Design | ||
RegionServer Sizing Rules of Thumb | ||
HBase and MapReduce | ||
Securing Apache HBase | ||
Architecture | ||
In-memory Compaction | ||
Backup and Restore | ||
Synchronous Replication | ||
Apache HBase APIs | ||
Apache HBase External APIs | ||
Thrift API and Filter Language | ||
HBase and Spark | @TsingJyujing | |
Apache HBase Coprocessors | ||
Apache HBase Performance Tuning | ||
Troubleshooting and Debugging Apache HBase | ||
Apache HBase Case Studies | ||
Apache HBase Operational Management | ||
Building and Developing Apache HBase | ||
Unit Testing HBase Applications | ||
Protobuf in HBase | ||
Procedure Framework (Pv2): HBASE-12439 | ||
AMv2 Description for Devs | ||
ZooKeeper | ||
Community | ||
Appendix |
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深度学习 TensorFlow - 第1期
- 【推荐】深度学习 TensorFlow 从0~1入门
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