{"id":13415764,"url":"https://github.com/spro/practical-pytorch","last_synced_at":"2025-03-14T23:31:05.845Z","repository":{"id":45668013,"uuid":"79684696","full_name":"spro/practical-pytorch","owner":"spro","description":"Go to https://github.com/pytorch/tutorials - this repo is deprecated and no longer maintained","archived":true,"fork":false,"pushed_at":"2021-07-01T04:34:00.000Z","size":1713,"stargazers_count":4538,"open_issues_count":90,"forks_count":1103,"subscribers_count":146,"default_branch":"master","last_synced_at":"2025-03-11T05:52:56.905Z","etag":null,"topics":["natural-language-generation","natural-language-processing","nlg","nlp","seq2seq"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/spro.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2017-01-22T01:28:10.000Z","updated_at":"2025-03-07T08:27:31.000Z","dependencies_parsed_at":"2022-08-12T12:00:24.968Z","dependency_job_id":null,"html_url":"https://github.com/spro/practical-pytorch","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/spro%2Fpractical-pytorch","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/spro%2Fpractical-pytorch/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/spro%2Fpractical-pytorch/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/spro%2Fpractical-pytorch/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/spro","download_url":"https://codeload.github.com/spro/practical-pytorch/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243663450,"owners_count":20327299,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["natural-language-generation","natural-language-processing","nlg","nlp","seq2seq"],"created_at":"2024-07-30T21:00:51.960Z","updated_at":"2025-03-14T23:31:05.177Z","avatar_url":"https://github.com/spro.png","language":"Jupyter Notebook","funding_links":[],"categories":["Jupyter Notebook","Tutorials \u0026 books \u0026 examples｜教程 \u0026 书籍 \u0026 示例","Tutorials, books, \u0026 examples","Data Science","Codes","Tutorials \u0026 Examples"],"sub_categories":["Other libraries｜其他库:","Other libraries:"],"readme":"**These tutorials have been merged into [the official PyTorch tutorials](https://github.com/pytorch/tutorials). Please go there for better maintained versions of these tutorials compatible with newer versions of PyTorch.**\n\n---\n\n![Practical Pytorch](https://i.imgur.com/eBRPvWB.png)\n\nLearn PyTorch with project-based tutorials. These tutorials demonstrate modern techniques with readable code and use regular data from the internet.\n\n## Tutorials\n\n#### Series 1: RNNs for NLP\n\nApplying recurrent neural networks to natural language tasks, from classification to generation.\n\n* [Classifying Names with a Character-Level RNN](https://github.com/spro/practical-pytorch/blob/master/char-rnn-classification/char-rnn-classification.ipynb)\n* [Generating Shakespeare with a Character-Level RNN](https://github.com/spro/practical-pytorch/blob/master/char-rnn-generation/char-rnn-generation.ipynb)\n* [Generating Names with a Conditional Character-Level RNN](https://github.com/spro/practical-pytorch/blob/master/conditional-char-rnn/conditional-char-rnn.ipynb)\n* [Translation with a Sequence to Sequence Network and Attention](https://github.com/spro/practical-pytorch/blob/master/seq2seq-translation/seq2seq-translation.ipynb)\n* [Exploring Word Vectors with GloVe](https://github.com/spro/practical-pytorch/blob/master/glove-word-vectors/glove-word-vectors.ipynb)\n* *WIP* Sentiment Analysis with a Word-Level RNN and GloVe Embeddings\n\n#### Series 2: RNNs for timeseries data\n\n* *WIP* Predicting discrete events with an RNN\n\n## Get Started\n\nThe quickest way to run these on a fresh Linux or Mac machine is to install [Anaconda](https://www.continuum.io/anaconda-overview):\n```\ncurl -LO https://repo.continuum.io/archive/Anaconda3-4.3.0-Linux-x86_64.sh\nbash Anaconda3-4.3.0-Linux-x86_64.sh\n```\n\nThen install PyTorch:\n\n```\nconda install pytorch -c soumith\n```\n\nThen clone this repo and start Jupyter Notebook:\n\n```\ngit clone http://github.com/spro/practical-pytorch\ncd practical-pytorch\njupyter notebook\n```\n\n## Recommended Reading\n\n### PyTorch basics\n\n* http://pytorch.org/ For installation instructions\n* [Offical PyTorch tutorials](http://pytorch.org/tutorials/) for more tutorials (some of these tutorials are included there)\n* [Deep Learning with PyTorch: A 60-minute Blitz](http://pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html) to get started with PyTorch in general\n* [Introduction to PyTorch for former Torchies](https://github.com/pytorch/tutorials/blob/master/Introduction%20to%20PyTorch%20for%20former%20Torchies.ipynb) if you are a former Lua Torch user\n* [jcjohnson's PyTorch examples](https://github.com/jcjohnson/pytorch-examples) for a more in depth overview (including custom modules and autograd functions)\n\n### Recurrent Neural Networks\n\n* [The Unreasonable Effectiveness of Recurrent Neural Networks](http://karpathy.github.io/2015/05/21/rnn-effectiveness/) shows a bunch of real life examples\n* [Deep Learning, NLP, and Representations](http://colah.github.io/posts/2014-07-NLP-RNNs-Representations/) for an overview on word embeddings and RNNs for NLP\n* [Understanding LSTM Networks](http://colah.github.io/posts/2015-08-Understanding-LSTMs/) is about LSTMs work specifically, but also informative about RNNs in general\n\n### Machine translation\n\n* [Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation](http://arxiv.org/abs/1406.1078)\n* [Sequence to Sequence Learning with Neural Networks](http://arxiv.org/abs/1409.3215)\n\n### Attention models\n\n* [Neural Machine Translation by Jointly Learning to Align and Translate](https://arxiv.org/abs/1409.0473)\n* [Effective Approaches to Attention-based Neural Machine Translation](https://arxiv.org/abs/1508.04025)\n\n### Other RNN uses\n\n* [A Neural Conversational Model](http://arxiv.org/abs/1506.05869)\n\n### Other PyTorch tutorials\n\n* [Deep Learning For NLP In PyTorch](https://github.com/rguthrie3/DeepLearningForNLPInPytorch)\n\n## Feedback\n\nIf you have ideas or find mistakes [please leave a note](https://github.com/spro/practical-pytorch/issues/new).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fspro%2Fpractical-pytorch","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fspro%2Fpractical-pytorch","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fspro%2Fpractical-pytorch/lists"}