NLTK Alternatives

NLTK reviews and mentions

• Best Portfolio Projects for Data Science
  3 projects | dev.to | 19 Sep 2023

  NLTK Documentation

• Can an average person learn how to build a LLM model?
  2 projects | /r/deeplearning | 23 Apr 2023

  But if you want to learn start with NLTK, it's a free course and book in python that will give you a solid foundation in NLP.

• Show HN: SiteGPT – Create ChatGPT-like chatbots trained on your website content
  7 projects | news.ycombinator.com | 1 Apr 2023

  Not to go full "Dropbox in a weekend", but if you're technical enough to self-host, this is something you can build for yourself

  Everyone is going straight to embeddings, but it'd be easy enough to use old school NLP summarization from NLTK (https://www.nltk.org/)

  Hook that up a web scraping library like https://scrapy.org/ and get a summary of each page.

  Then embed a site map in your system prompt and use langchain (https://github.com/hwchase17/langchain) to allow GPT to query for a specific page's summary.

  -

  The point of this isn't to say that's how OP did it, but there might be people seeing stuff like this and wondering how on earth to get into it: This is something you could build in a weekend with pretty much no understanding of AI

• Learn more about spell checkers
  2 projects | /r/nlp_knowledge_sharing | 18 Mar 2023

  Books: a. "Speech and Language Processing" by Daniel Jurafsky and James H. Martin (3rd Edition) - This book covers various aspects of natural language processing, including a section on spelling correction that provides a comprehensive introduction to the topic. b. "Foundations of Statistical Natural Language Processing" by Christopher D. Manning and Hinrich Schütze - This book provides an overview of statistical approaches in NLP, including a chapter on spelling correction. Articles: a. "How to Write a Spelling Corrector" by Peter Norvig - This article demonstrates the development of a simple spelling corrector using statistical algorithms. It's a great starting point for understanding the basics of spell checkers. (Link: https://norvig.com/spell-correct.html) b. "The Design of a Proofreading Software Service" by Michael D. Garris and James L. Blue - This article presents the design and implementation of a spelling correction system that can be integrated into various applications. (Link: https://www.nist.gov/system/files/documents/itl/iad/89403123.pdf) c. "A Fast and Flexible Spellchecker" by Atkinson, K. (2006) - This article details the design of a spell checker that uses a combination of rule-based and statistical approaches for improved performance. (Link: https://aspell.net/0.60.6.1/aspell-0.60.6.1.pdf) Online Resources: a. The Natural Language Toolkit (NLTK) - This is a popular Python library for natural language processing. It includes a spell checker module and various examples of how to use it. (Link: https://www.nltk.org/) b. SymSpell - This is an open-source spell checking library that uses a Symmetric Delete spelling correction algorithm for high performance and accuracy. The GitHub repository includes a detailed description of the algorithm and examples of how to use it. (Link: https://github.com/wolfgarbe/SymSpell) These resources should provide a solid foundation for understanding the design, algorithms, and usage of spell checkers. Happy learning!

• 10 Coding Projects to Impress Employers and Land Your Dream Job 😎
  13 projects | dev.to | 18 Feb 2023

  Natural Language Toolkit (NLTK) - a popular library for working with human language data in Python

• Unprompted [txt2mask] now works with Inpaint Sketch mode, can generate synonyms/antonyms, and even build custom GUIs! 🤯
  3 projects | /r/StableDiffusion | 28 Jan 2023

  Next, there's a bunch of new natural language processing features. With the power of NLTK and the Moby Thesaurus, you can now find synonyms, antonyms, hypernyms, and hyponyms for any text. Once the word databases are downloaded to your machine, an internet connection is not required to use these features.

• Training on BERT without any 'context' just questions/answer tuples?
  2 projects | /r/LanguageTechnology | 10 Dec 2022

  (1) For large scale processing/tokenizing your data I would consider using something like NLTK or Spacy. That's if your books are already in text form. If they are scans, you'll need to use some OCR software first.

• Estimation of text complexity
  3 projects | dev.to | 24 Nov 2022

  NLTK: for token processing

• Has anyone here ever used the seaNMF model for short text topic modeling, and be willing to help me get started with it?
  4 projects | /r/LanguageTechnology | 24 Nov 2022

  Tokenize with NLTK, SpaCy or CoreNLP

• I'm Al Sweigart, author of several free programming books. My latest book is on recursion and recursive algorithms. AMA!
  4 projects | /r/IAmA | 12 Sep 2022

  Check out the NLTK library, if you need some guidance or ideas what you can do with it check out Jurafsky's excellent book which is also free.

• A note from our sponsor - Onboard AI
  getonboard.dev | 1 Dec 2023

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