mixed-naive-bayes
twitter-stock-sentiment
| mixed-naive-bayes | twitter-stock-sentiment | |
|---|---|---|
| 1 | 1 | |
| 63 | 9 | |
| - | - | |
| 2.5 | 0.0 | |
| about 1 year ago | about 3 years 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.
mixed-naive-bayes
-
[Discussion] Unique uses of recommendation systems?
Some of the features are categorical, such as request type (is it about troubleshoot, price request, etc.), product, language, SLA, etc.; and some are continuous, namely an embedding vector generated from the ticket free form text. Then we use this library that allows the training of a Naive Bayes model using mixed type of features (categorical and continuous).
twitter-stock-sentiment
What are some alternatives?
system-design-primer - Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
stocksight - Stock market analyzer and predictor using Elasticsearch, Twitter, News headlines and Python natural language processing and sentiment analysis
tabmat - Efficient matrix representations for working with tabular data
Twitter-Sentiment-Analysis-API - Sentiment analysis web application and rest api implementation using django and NLTK.
News-Sense - A Streamlit app based on Python that fetches top news articles from the News API, generates a summary of each article using the OpenAI GPT-3 model, analyzes the sentiment of the article using the NLTK library, and classifies the article into different categories based on keywords.