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This repository contains the codebase used in the research conducted for the paper titled "Benchmarking Cryptocurrency Forecasting Models in the Context of Data Properties and Market Factors." The study involved a rigorous assessment of thirteen different time series forecasting models over twenty-one cryptocurrencies and four distinct time frames.
Example of Prophet (Meta/Facebook) library usage. Utilizing the powerful Prophet library, this project offers robust time series forecasting capabilities. With comprehensive documentation and a streamlined setup process tailored for Linux systems, users can seamlessly automate predictions using cron jobs, enhancing efficiency in forecasting tasks.
🏡 Previsão de Preços Imobiliários com Ciência de Dados 📈💰 Desenvolvi uma aplicação web, usando Flask, Python, HTML e CSS para um modelo de machine learning que desenvolvi, no qual faz a previsão(estimada) do valor dos imóveis em 2 cidades da Paraíba: João Pessoa e Cabedelo.
Property Rent Price Estimation in Paris by analyzing capacity, facility, location, and other related features of 50.132 hotels, apartments, and other accommodation services in all Paris’ neighborhoods.
The code implements a neural network model, PricePredictor, trained on historical stock price data to predict future stock prices, visualizing the predictions alongside historical prices and calculating the average of the predicted prices.
This is a price prediction system where we can predict the current price of certain items. The items include Car, Gold, Bitcoin, Mobile and Avocado price.