Sentiment Analysis
Showing 36 of 39 projects
An open-source framework for financial large language models, enabling cost-effective fine-tuning for tasks like sentiment analysis and forecasting.
A simple Python framework for state-of-the-art natural language processing (NLP) tasks like named entity recognition and sentiment analysis.
A simple Python framework for state-of-the-art natural language processing (NLP) tasks like named entity recognition and sentiment analysis.
A Python web mining module with tools for scraping, NLP, machine learning, network analysis, and visualization.
A Python library for processing simplified Chinese text, offering sentiment analysis, segmentation, and keyword extraction.
A modular natural language processing library for Node.js and React Native, designed for building multilingual chatbots and language utilities.
A Python bot that analyzes Trump tweets for company mentions, performs sentiment analysis, and automatically executes stock trades.
A complete AI-driven process using GANs with LSTM and CNN to predict stock price movements, incorporating diverse data sources and hyperparameter optimization.
A state-of-the-art Natural Language Processing library built on Apache Spark, offering 100,000+ pretrained models and pipelines in 200+ languages.
A Rust-native port of Hugging Face Transformers providing ready-to-use NLP pipelines and transformer models like BERT, GPT2, and T5.
An open-source Java framework for rapid development of machine learning and statistical applications with large dataset support.
A curated list of awesome resources, libraries, and tools for natural language processing (NLP) in Ruby.
A curated list of awesome resources, libraries, and tools for natural language processing (NLP) in Ruby.
An open-source suite featuring financial large language models (FinMA), instruction datasets (FIT), and evaluation benchmarks (FinBen) for financial AI.
A Ruby library for text classification with Bayesian, LSI, logistic regression, k-NN, and TF-IDF algorithms.
A Ruby gem for simple sentiment analysis that classifies text as positive, negative, or neutral based on configurable thresholds.
A Node.js sample application demonstrating the IBM Watson Tone Analyzer service for detecting emotional and language tones in text.
A curated collection of datasets, corpora, and resources for Indonesian natural language processing tasks.
A real-time sentiment analysis and visualization tool for social media data, rendering live charts to identify trends.
A real-time Bitcoin price prediction system using LSTM models and Twitter sentiment analysis.
A comprehensive Natural Language Processing (NLP) library for the Crystal programming language.
A curated collection of open-source libraries, models, datasets, and tools for Natural Language Processing (NLP) in Norwegian.
Sentiment Classification using Word Sense Disambiguation
Bayesian text classifier for Go with flexible tokenizers and storage backends.
A Node.js sample application demonstrating IBM Watson Natural Language Understanding service features.
A Python library providing German language support for TextBlob, enabling NLP tasks like tokenization, POS tagging, and sentiment analysis.
TensorFlow implementation of hierarchical attention networks for document classification using GRU cells and attention mechanisms.
Simple sentiment analysis for Elixir based on AFINN-165 with emoji, booster, and negator support.
A Blazor library that provides easy access to ML5.js machine learning models via JavaScript Interop.
A pre-trained BERT-based model for detecting positive or negative sentiment in short text fragments.
A Go port of VADER sentiment analysis for scoring text sentiment (positive, negative, neutral, compound).
Elixir library for sentiment analysis using the AFINN-111 word list.
A Ruby implementation of Naive Bayes text classification designed as a strategy for the OmniCat classification framework.
A Ruby gem for performing sentiment analysis on German text using dictionary-based scoring.
A simple and extensible Ruby gem for sentiment analysis with customizable analysis strategies.
A Swift playground for sentiment analysis using AFINN-165 wordlist and Emoji Sentiment Ranking.
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