redditflow
spaCy
redditflow | spaCy | |
---|---|---|
7 | 106 | |
82 | 28,751 | |
- | 0.6% | |
0.0 | 9.2 | |
7 months ago | 6 days ago | |
Python | Python | |
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.
redditflow
- [p] I helped a researcher build everything from data collection to model building, and open sourced it.
- I built an AI tool to help a researcher build everything from data collection to model building, and open sourced it.
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Nfflow/Redditflow: An AI tool that handles everything from data collection to model building in two lines of code!
I once worked with a researcher who was struggling with some python code, and she was trying to scrape data and have ML models trained on the data. After seeing her struggle, I decided to build an organization where I can do everything end to end data collection to model training. As part of the mission, I am releasing redditflow, the first product to solve our mission. With only the help of two lines of python code, Redditflow uses the Reddit API to scrape any image or text data from any timeline from past to future, and AI algorithms will filter the scraped data, and finally, train an ML model as output! Github: https://github.com/nfflow/redditflow Please raise an issue, join discord at https://discord.gg/8u362Yc3 or mail me at [[email protected]](mailto:[email protected]) if you would like to contribute! I will be excited to talk with you!
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GitHub - nfflow/redditflow: An AI tool to automate everything from data collection to model training, in two lines of python!
Github: https://github.com/nfflow/redditflow
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What are the best tools which handle everything from data collection (Via scraping) to filtering the data and training an ML model as output?
P.S : I have attempted to solve this via the reddit API in :https://github.com/nfflow/redditflow.
- I made a tool for building ML models from reddit data from any timeline from past to future!
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Redditflow- Find data from any timeline from past to future and feed your ML pipelines
Well, there's a lot we can do for the community through open source. We welcome all contributions which will help us move forward a step in helping making the data science process simpler. Check out https://github.com/nfflow/redditflow
spaCy
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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/
- Swirl: An open-source search engine with LLMs and ChatGPT to provide all the answers you need 🌌
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How to predict this sequence?
spaCy
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What do you all think about (setq sentence-end-double-space nil)?
I chose spacy. Although it's not state of the art, it's very well established and stable.
- spaCy: Industrial-Strength Natural Language Processing
What are some alternatives?
pubmedflow - Data Collection API for pubmed
TextBlob - Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.
Stanza - Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
NLTK - NLTK Source
BERT-NER - Pytorch-Named-Entity-Recognition-with-BERT
polyglot - Multilingual text (NLP) processing toolkit
textacy - NLP, before and after spaCy
Jieba - 结巴中文分词
PyTorch-NLP - Basic Utilities for PyTorch Natural Language Processing (NLP)
CoreNLP - CoreNLP: A Java suite of core NLP tools for tokenization, sentence segmentation, NER, parsing, coreference, sentiment analysis, etc.
Pattern - Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.
duckling - Language, engine, and tooling for expressing, testing, and evaluating composable language rules on input strings.