A Python project that uses natural language processing and machine learning to classify text into positive, negative, or neutral sentiments also combines Sentiment Analysis and Long Short-Term Memory (LSTM) networks to predict the future trends of stocks. By analyzing sentiment from financial news and using advanced deep learning techniques, the system aims to provide insights into potential market movements.
🔍 Key Features:
- Sentiment Analysis: Utilize Natural Language Processing (NLP) techniques to analyze sentiment from financial news articles and social media.
- LSTM Predictions: Implement Long Short-Term Memory (LSTM) neural networks to capture intricate patterns in stock price data and make future predictions.
- Data Preprocessing: Clean, preprocess, and integrate financial data for effective model training.
- Visualizations: Provide interactive visualizations of sentiment trends, stock prices, and predicted future trends.