Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis and Stock-Market-Prediction
About Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis
kaushikjadhav01/Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis
Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code). The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are made using three algorithms: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices of the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall
This web application helps individual investors and traders forecast stock prices and receive recommendations. You input a stock ticker from NASDAQ or NSE, and it outputs predictions for the next seven days, along with a recommendation on whether the price is likely to rise or fall, based on both price trends and social media sentiment. It's designed for anyone managing their own stock portfolio or making short-term trading decisions.
About Stock-Market-Prediction
madhurimarawat/Stock-Market-Prediction
This repository began as a 7th-semester minor project and evolved into our 8th-semester major project, "Advanced Stock Price Forecasting Using a Hybrid Model of Numerical and Textual Analysis." It utilizes Python, NLP (NLTK, spaCy), ML models, Grafana, InfluxDB, and Streamlit for data analysis and visualization.
This project helps individual investors, traders, or financial analysts forecast stock prices by combining historical numerical data with insights from financial news. It takes in historical stock prices and financial news articles, processes them using machine learning, and outputs predictions and visualizations of stock price movements. This tool is designed for anyone looking to make more informed decisions about buying or selling stocks.
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