Time Series forecasting and linear regression modelling of currency price action
Timeseries Analysis of Dallas zipcodes based on forcasted ROI
A popular and widely used statistical method for time series forecasting is the ARIMA model. It is one of the most popular models to predict linear time series data. This model has been used to predict the electricity price for Spain Market.
Times_Series_Analysis_with_ARIMA
This project involves analyzing unemployment rates during the COVID-19 pandemic. The goal is to understand the trends and forecast future unemployment rates using time series analysis. The project includes data cleaning, visualization, and ARIMA modeling.
Time Series forecasting and linear regression modelling of currency price action.
An R/Shiny application created to help users practice ARIMA time series modelling. Hosted on AWS EC2.
A comprehensive time series analysis of French retail quarterly sales data from 2012 to 2017. The project focuses on analyzing sales patterns, seasonal decomposition, and trend analysis using various statistical techniques and visualizations.
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