nlp-recipes
nlp_course
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| nlp-recipes | nlp_course | |
|---|---|---|
| 5 | 6 | |
| 6,020 | 9,430 | |
| - | 1.3% | |
| 0.0 | 8.7 | |
| over 1 year ago | about 2 months ago | |
| Python | Jupyter Notebook | |
| MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
nlp-recipes
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Show HN: I turned my microeconomics textbook into a chatbot with GPT-3
https://github.com/topics/automatic-summarization
Microsoft/nlp-recipes lists current NLP tasks that would be helpful for a docs bot: https://github.com/microsoft/nlp-recipes#content
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Show HN: DocsGPT, open-source documentation assistant, fully aware of libraries
https://github.com/topics/automatic-summarization
Though now archived,
> Microsoft/nlp-recipes lists current NLP tasks that would be helpful for a docs bot: https://github.com/microsoft/nlp-recipes#content
NLP Tasks: Text Classification, Named Entity Recognition, Text Summarization, Entailment, Question Answering, Sentence Similarity, Embeddings, Sentiment Analysis, Model Explainability, and Auto-Annotatiom
- ✨ 5 Free Resources for Learning Natural Language Processing with Python 🚀
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Is there any utility software/bot that produces descriptor tags for a Reddit image post using the comments?
I found this (https://github.com/microsoft/nlp-recipes) resource and it has a list of pre-built or easily customizable NLP models that I'm going to try out.
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Building a Aspect based sentiment classification
There is an NLP recipe from Microsoft on ABSA. Have you seen this? https://github.com/microsoft/nlp-recipes/blob/master/examples/sentiment_analysis/absa/absa.ipynb
nlp_course
- NLP Course – For You
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✨ 5 Free Resources for Learning Natural Language Processing with Python 🚀
🔗 https://github.com/yandexdataschool/nlp_course
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Need help finding good NLP course
For a better understanding of the theory and science behind the nlp methods and models, including transformers, I can recommend this one: https://lena-voita.github.io/nlp_course.html Lots of neat visualizations and intuitive explanations, practical exercises and links to influential nlp papers.
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Any good resources to go from RNNs to transformers covering all the evolved architecture between them?
This NLP course for you in blog format covers most of the materials from word2vec to pretrained transformer models and fine-tuning. The visuals are really good and I found them very helpful to understand some of the details.
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[Discussion] Any advanced NLP tutorial to refresh a veteran's memory?
Lena Voita's "NLP Course For You" is really cool and has nice visualizations and explanations.
- 11 Best Natural Language Processing Online Courses
What are some alternatives?
ludwig - Low-code framework for building custom LLMs, neural networks, and other AI models
awesome-nlp - :book: A curated list of resources dedicated to Natural Language Processing (NLP)
OpenPrompt - An Open-Source Framework for Prompt-Learning.
nlp-tutorial - Natural Language Processing Tutorial for Deep Learning Researchers
rasa - 💬 Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants
course-nlp - A Code-First Introduction to NLP course
deepsegment - A sentence segmenter that actually works!
nlp-in-python-tutorial - comparing stand up comedians using natural language processing
pymarl2 - Fine-tuned MARL algorithms on SMAC (100% win rates on most scenarios)
Parrot_Paraphraser - A practical and feature-rich paraphrasing framework to augment human intents in text form to build robust NLU models for conversational engines. Created by Prithiviraj Damodaran. Open to pull requests and other forms of collaboration.
ccg2lambda - Provide Semantic Parsing solutions and Natural Language Inferences for multiple languages following the idea of the syntax-semantics interface.
link-grammar - The CMU Link Grammar natural language parser