process-google-dataset
spaCy
| process-google-dataset | spaCy | |
|---|---|---|
| 1 | 111 | |
| 33 | 31,423 | |
| - | 1.4% | |
| 0.0 | 8.8 | |
| over 3 years ago | 15 days ago | |
| JavaScript | Python | |
| GNU General Public License v3.0 only | MIT License |
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process-google-dataset
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Image Repository - Gesture Recognition
Repo: https://github.com/masesk/process-google-dataset
spaCy
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15,000 lines of verified cryptography now in Python
Geez honestly
This seems to be the issue https://github.com/explosion/spaCy/issues/13658#issuecomment...
And you depend on opinionated libraries that break with newer versions. Why? Well because f you that's why! Because our library is not just a tool, it's a lifestyle
Though it seems that Pydantic 1x does support 3.13 https://docs.pydantic.dev/1.10/changelog/#v11020-2025-01-07
- SpaCy – Industrial-Strength Natural Language Processing in Python
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350M Tokens Don't Lie: Love and Hate in Hacker News
Is this just using LLM to be cool? How does pure LLM with simple "In the scale between 0-10"" stack up against traditional, battle-tested sentiment analysis tools?
Gemini suggests NLTK and spaCy
https://www.nltk.org/
https://spacy.io/
- How I discovered Named Entity Recognition while trying to remove gibberish from a string.
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Step by step guide to create customized chatbot by using spaCy (Python NLP library)
Hi Community, In this article, I will demonstrate below steps to create your own chatbot by using spaCy (spaCy is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython):
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Best AI SEO Tools for NLP Content Optimization
SpaCy: An open-source library providing tools for advanced NLP tasks like tokenization, entity recognition, and part-of-speech tagging.
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Who has the best documentation you’ve seen or like in 2023
spaCy https://spacy.io/
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A beginner’s guide to sentiment analysis using OceanBase and spaCy
In this article, I'm going to walk through a sentiment analysis project from start to finish, using open-source Amazon product reviews. However, using the same approach, you can easily implement mass sentiment analysis on your own products. We'll explore an approach to sentiment analysis with one of the most popular Python NLP packages: spaCy.
- Retrieval Augmented Generation (RAG): How To Get AI Models Learn Your Data & Give You Answers
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Against LLM Maximalism
Spacy [0] is a state-of-art / easy-to-use NLP library from the pre-LLM era. This post is the Spacy founder's thoughts on how to integrate LLMs with the kind of problems that "traditional" NLP is used for right now. It's an advertisement for Prodigy [1], their paid tool for using LLMs to assist data labeling. That said, I think I largely agree with the premise, and it's worth reading the entire post.
The steps described in "LLM pragmatism" are basically what I see my data science friends doing — it's hard to justify the cost (money and latency) in using LLMs directly for all tasks, and even if you want to you'll need a baseline model to compare against, so why not use LLMs for dataset creation or augmentation in order to train a classic supervised model?
[0] https://spacy.io/
[1] https://prodi.gy/
What are some alternatives?
blackjack-basic-strategy - A computer vision powered Blackjack basic strategy app powered by Roboflow.
Stanza - Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
picovoice - On-device voice assistant platform powered by deep learning
NLTK - NLTK Source
live-digit-recognition - 🔢 Computer will recognize the digits you wrote on a beautiful web-interface
TextBlob - Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.