Stock price prediction using Bidirectional LSTM and sentiment analysis
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Updated
Sep 9, 2018 - JavaScript
Stock price prediction using Bidirectional LSTM and sentiment analysis
A data engineering course that focuses on how to create a real-time Twitter analytics dashboard for streaming tweets with a sentiment analysis (NLP) feature.
Like and retweet your tweets, or search tweets by topic. It stores and serves data with a Flask webapp. 🐦 Live demo running on twitter.com/ai_testing
An off-the-shelf pre-trained Tweet NLP Toolkit (NER, tokenization, lemmatization, POS tagging, dependency parsing) + Tweebank-NER dataset
This is a web-app which employs the citizen science program by tracking their tweets and subsequent data analysis on Google Earth Engine, aimed at effective CyanoHAB detection and monitoring in water bodies around the world.
How Will Your Tweet Be Received? Predicting theSentiment Polarity of Tweet Replies
Hashformers is a framework for hashtag segmentation with Transformers and Large Language Models (LLMs).
Implementation of an ETL process for real-time sentiment analysis of tweets with Docker, Apache Kafka, Spark Streaming, MongoDB and Delta Lake
twig.py - a twitter web3 influencer truffle pig used for finding engaged users
Blazing fast topic modelling for short texts.
👍🏻 👎🏻 Applying data analysis and comparing machine learning algorithms in their efficiency in predicting the sentiment(positive/negative/neutral) of tweets.
Music for your Mood! Tweet at us and we got you covered!
Analysing Of Tweet Sentiments Using Supervised Learning Classification Algorithms
Sentiment Analysis of tweets written in underused Slavic languages (Serbian, Bosnian and Croatian) using pretrained multilingual RoBERTa based model XLM-R on 2 different datasets.
This repository contains the NLP and Text Mining R script and the generated charts namely Sentiment Pie chart, Emotion Bar chart and Word Cloud chart.
CoviSA is a Visualization Dashboard for analyzing the Sentiments and Emotions related to COVID-19 Tweets.The project fetched data from Twitter and analysed it using a ML Model. The web app is developed with ReactJS served over a Flask server.
Análises utilizadas para treino dos modelos Naive Bayes, SVM e Decision Three no meu Trabalho de Conclusão de Curso na Universidade Unit
Sentiment Analysis on Loksabha Elections 2019
FinABSA is a T5-Large model trained for Aspect-Based Sentiment Analysis specifically for financial domains.
Python package to clean raw tweets for ML applications.
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