awesome-sentiment-analysis
n4m-sentiment
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| awesome-sentiment-analysis | n4m-sentiment | |
|---|---|---|
| 1 | 1 | |
| 526 | 10 | |
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| 1.9 | 0.0 | |
| 6 months ago | almost 3 years ago | |
| Max | ||
| - | GNU General Public License v3.0 or later |
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awesome-sentiment-analysis
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What are the ways to handle out of domain inputs for text classification?
Get or generate negative class data. There are adversarial approaches that can improve domain generalization, but it's best to acquire more data from diverse sources. You mentioned you're working on sentiment in one of your comments- there are a ton of open-source sentiment datasets, at least for English, comprising millions of rows of data. Randomly sample from a wide variety of them to hit as many domains as possible. It's also worth including a neutral class.
n4m-sentiment
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n4m-sentiment : sentiment analysis for MaxMSP
Download it for free here: https://github.com/lysdexic-audio/n4m-sentiment
What are some alternatives?
awesome-hungarian-nlp - A curated list of NLP resources for Hungarian
pytorch-sentiment-analysis - Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
obsei - 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 .
bulbea - :boar: :bear: Deep Learning based Python Library for Stock Market Prediction and Modelling
Sentiment - An example project using a feed-forward neural network for text sentiment classification trained with 25,000 movie reviews from the IMDB website.
afinn - AFINN sentiment analysis in Python
n4m-handpose - Wraps MediaPipe HandPose inside electron and serves the detected parts via MaxAPI.
nlphose - Enables creation of complex NLP pipelines in seconds, for processing static files or streaming text, using a set of simple command line tools. Perform multiple operation on text like NER, Sentiment Analysis, Chunking, Language Identification, Q&A, 0-shot Classification and more by executing a single command in the terminal. Can be used as a low code or no code Natural Language Processing solution. Also works with Kubernetes and PySpark !
Blind-App-Reviews - Scraped reviews of over 25 companies from the Blind App ⚡️
financial-news-dataset - Reuters and Bloomberg