What_you_say
Natural language detection library. Written in Rust, wrapped in Ruby.
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Text Analytics With Python | 1,073 | 3 years ago | apache-2.0 | Jupyter Notebook | ||||||
| Learn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, "Text Analytics with Python" published by Apress/Springer. | ||||||||||
| Obsei | 1,020 | 3 months ago | 14 | November 19, 2022 | 31 | apache-2.0 | Python | |||
| Obsei is a low code AI powered automation tool. It can be used in various business flows like social listening, AI based alerting, brand image analysis, comparative study and more . | ||||||||||
| Whatlang Rs | 919 |  | 12 | 14 | 4 months ago | 33 | August 16, 2023 | 10 | mit | Rust |
| Natural language detection library for Rust. Try demo online: https://whatlang.org/ | ||||||||||
| Meta | 660 | a year ago | 54 | mit | C++ | |||||
| A Modern C++ Data Sciences Toolkit | ||||||||||
| Text_mining_resources | 511 | a year ago | ||||||||
| Resources for learning about Text Mining and Natural Language Processing | ||||||||||
| Artificial Adversary | 317 |  | 1 | 6 years ago | 3 | August 29, 2018 | 7 | mit | Python | |
| 🗣️ Tool to generate adversarial text examples and test machine learning models against them | ||||||||||
| Fake_news_detection | 251 | 2 years ago | 10 | mit | Jupyter Notebook | |||||
| Fake News Detection in Python | ||||||||||
| Textvec | 190 | 4 months ago | 4 | December 03, 2020 | 4 | mit | Python | |||
| Text vectorization tool to outperform TFIDF for classification tasks | ||||||||||
| Awesome Text Classification | 144 | 6 years ago | apache-2.0 | |||||||
| Awesome-Text-Classification Projects,Papers,Tutorial . | ||||||||||
| Support Tickets Classification | 128 | 3 years ago | 4 | mit | Python | |||||
| This case study shows how to create a model for text analysis and classification and deploy it as a web service in Azure cloud in order to automatically classify support tickets. This project is a proof of concept made by Microsoft (Commercial Software Engineering team) in collaboration with Endava http://endava.com/en | ||||||||||
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Ruby
Text Classification
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