This repository introduces some basics on time series. It also presents ARIMA models and its variants as well as the Facebook Prophet forecasting model.

Forecasting Exercises done in R

This Project analyses the carbon footprint of the U.S. commercial sector using three machine learning models. A combination of energy consumption data and carbon dioxide emission data was used to achieve the carbon footprint variable.

Prophet Based Weather Forecasting Miniproject

stock value prediction with pyhton

We, the Green-Hawk team, are competing in the NASA Space App Challenge 2021 under the theme "WARNING: THINGS ARE HEATING UP!".  We used time series analysis and forecasting to forecast how our beloved planet's temperature will change over the next 100 years.

Predict future stock prices with this Streamlit web app. Choose a company, set the forecast period, and visualize historical data and forecasted trends. Powered by machine learning with the Prophet library. Try it now!

In this section, we will examine the use of the prophet method, which is one of the time series analysis methods.

A comprehensive machine learning project using Facebook's Prophet to forecast future sales. The model utilized historical data and effectively accounted for various factors, including seasonality effects, demand fluctuations, holiday impacts, promotional activities, and competitive influences.

A time-series forecasting model in Prophet for projection of business potential data.

Air quality index with Prophet - Tutorial

The aim of this repo is to predict forecast for the future of a specific area, where up to 30 years forecast being predicted using Prophet Model.

Training time-series prediction models to predict future avocado prices using Prophet

Streamlit Data Web Application using Facebook’s forecasting algorithm - Prophet

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.

This project analyzes and forecasts Superstore sales data for furniture and office supplies using time series models like ARIMA and Facebook's Prophet, highlighting seasonal patterns and trends.

Retail Store Demand Forecasting

Basic machine learning project for predicting stocks

Batch Name: MIP-ML-11 (Machine Learning Intern)