Using Transformer deep learning architecture to predict stock prices.

Reproduction of code described in the paper "Stock Market Prediction Based on Generative Adversarial Network" by Kang Zhang et al.

Stock Market Forecasting with CoreML in Swift

The main goal of this project is to predict future stock prices using a regression method. I have used two algorithms in this project to build a predictive model, i.e. PSO(Particle Swarm Optimization) and SVM(Support Vector Machine). PSO algorithm is a genetic population-based optimization algorithm that selects the future number using the paramet

A comprehensive project leveraging big data techniques for stock market prediction and analysis. This repository includes data collection, processing, and visualization tools, alongside machine learning models for predicting stock prices and analyzing market trends. Ideal for financial analytics and investment strategies.

web application for finding the best portfolio distribution for the total amount invested by investors in order to maximize their gains and minimize the risks.

Hidden Markov Model

An AI-driven stock analysis platform that leverages PyTorch LSTM models for price prediction, integrates real-time financial data APIs, and presents insights through interactive Streamlit dashboards, advanced visualizations, and professional market widgets. Fully Dockerized for scalable deployment.

I use this repository to publish a daily Python-based code. The goal is to learn Machine Learning/AI modelling by using daily posts

LSTM

This Streamlit-based web application predicts the closing price of stocks using historical data and a Random Forest model. Users can select any stock symbol, specify a date range, and enter stock features (Open, High, Low, Volume) to predict the closing price.