This repository hosts a stock market prediction model for Tesla and Apple using Liquid Neural Networks. It showcases data-driven forecasting techniques, feature engineering, and machine learning to enhance the accuracy of financial predictions.

📈 Stock market information with accurate and detailed statistical simulations for stocks using ChatGPT.

This repository features notebooks and datasets for predicting Tesla (TSLA) stock prices using LSTM models. Explore historical data, forecast trends, and gain insights into TSLA's market movements.

In this work an application of the Triple-Barrier Method and Meta-Labeling techniques is explored with XGBoost for the creation of a sentiment-based trading signal on the S&P 500 stock market index. The results confirm that sentiment data have predictive power, but a lot of work is to be carried out prior to implementing a strategy.

Stock Prediction System is a ML based website designed using Django's Framework and CSS's BootStrap Framework (NOTE: ALL THE DEPLOYMENTS ARE CURRENTLY DOWN)

This repository consists of the source code of the final project of CS 5100 Foundations of Artificial Intelligence.

The project involves analyzing the MASI index, representing the Moroccan stock market, to predict its future performance. The main objective is to develop a robust predictive model while identifying key factors influencing returns.

Market Analysis and Prediction

Stock Market Direction Predictor

This is an AI based project which specifically on Data domain. This Repository contains program which predicts share price for particular organization by data of past 60 days.

Web app to predict closing stock prices in real time using Facebook's Prophet time series algorithm with a multi-variate, single-step time series forecasting strategy.

The performance of SVR models highly depends upon the appropriate choice of SVR parameters. Here, different metaheuristic algorithms are used to tune the hyperparameters.

This repository contains my Social Networks Projects during University and the projects that I've implemented due to my interest in Social Networks. These projects include analysis of social networks like telegram and graph mining with NetworkX and Gephi and investigating the effect of social data on the stock market.

End to End self case study from Data Collection to Optimization for Deployment

Beginner-friendly collection of Python notebooks for various use cases of machine learning, deep learning, and analytics. For each notebook there is a separate tutorial on the relataly.com blog.

Astock

Stock market forecasting using Stacked LSTM

Stock market prediction on 5 italian companies using VAR model, OLS regressions and LSTM recurrent neural networks over data retrieved from Refinitiv Eikon

Stock Market Prediction on High-Frequency Data Using soft computing based AI models