Multi algorithm stock predictor built using Streamlit

Easy to follow stock price analysis on Indian stock data

Various Types of Stock Analysis in Excel, Matlab, Power BI, Python, R, and Tableau

Repository connected to streamlit cloud to monitor and push changes made in code to streamlit server.

Next-Generation Stock News Forecaster

LSTM model based stock price prediction

Machine learning project using LSTM networks to predict stock prices based on historical data from multiple companies.

Predict Stock is a stock market analysis tool that provides buy-sell alerts for multiple Borsa Istanbul (BIST) stocks. It uses advanced data analysis, machine learning, and sentiment analysis from real-time news to offer accurate, actionable insights.

predict the future of time series data

In this project i have tried to combine the following things: (notes, finance, transaction, stocks). In this project user can see the graph of the stock like grow site(but in worse conditions). Along with this my main purpose here is that user can enter the buy or sell orders and see what would have happened if he have buyed or selled that stocks.

This repository contains code for implementing both Large Language Models (LLM) and Long Short-Term Memory (LSTM) models in AWS SageMaker Studio Lab. It includes notebooks for LLM-based applications and LSTM models for stock price prediction.

PyTorch implementation of FactorVAE

The project aims to create a system that predict future possible stock prices or that has functionalities that has features to make predict easy.

A collections of Tradingview indicators and strategies built in Pinescript V5

The objective of this project is to develop a Long Short-Term Memory (LSTM) model to predict the closing prices of stocks listed on the Pakistan Stock Exchange (PSX). The model utilizes historical stock data to forecast future prices, providing valuable insights for investors and stakeholders.

Just trying to predict random stock using AR, MA, ARMA and ARIMA with Stationarity methodology .

This repository contains a comprehensive analysis of time series data (stock prices), forecasted using various statistical and deep learning models.