This project is about predicting stock prices with more accuracy using LSTM algorithm. For this project we have fetched real-time data from yfinance library.

This project implements a time series multivariate analysis using RNN/LSTM for stock price predictions. A deep RNN model was created and trained on five years ...

This GitHub repository hosts an advanced financial analysis project centered around predicting Uber's stock prices using Long Short-Term Memory (LSTM) ...

I will be considering the google stocks data and will create a LSTM network for prediction. Here we have two file train and test, having its google share ...

This project demonstrates the application of deep learning techniques to forecast Apple's stock prices using historical data from Yahoo Finance.

A deep learning model for predicting the next three closing prices of a stock, index, currency pair, etc. based on the past 10 days of trading history (Open, ...

This project combines Python and yfinance, leveraging LSTM in Keras for stock price predictions, hosted via a user-friendly platform with Streamlit for accurate ...

This Project is predicting stocks for 32 companies with error less than 1% using LSTM Networks. I have not used pre-built models. I have trained LSTM NN ...

This repository contains a Jupyter notebook that demonstrates how to use Long Short-Term Memory (LSTM) neural networks to predict stock prices for the S&P ...

This repository will consist of a Long Short-Term Memory implementation of a Recurrent Neural Network used to predict the stock prices of Google Stocks.