This report explores the application of deep learning for stock price prediction. It investigates the effectiveness of GRU neural networks in analyzing historical data to forecast closing prices for multiple companies.

Explore projects on stock price prediction using machine learning and a number recognition system built with deep learning. These highlight applications in predictive analytics and computer vision.

Stock Price Prediction uses machine learning and deep learning to forecast stock market trends from historical data. It applies time-series analysis, regression, and LSTM models for accurate predictions, with visualizations to interpret results. The project helps researchers and investors explore AI-driven financial forecasting.

This implements a stock price prediction model using LSTM neural networks. Fetches historical data from Yahoo Finance to predict future prices. Inspired by a YouTube tutorial, this project explores time series forecasting with deep learning techniques

This project explores stock price prediction using time series analysis. It compares the performance of LSTM, a deep learning model, with ARIMA, a statistical model. The focus is on forecasting HP Inc.'s future stock prices based on historical data. The aim is to highlight the strengths and weaknesses of both approaches in predicting stock trends.