Author : Miss.Ashwini Topre and Prof. Rajesh Bharati

In a country, economic growth indicators are measured by GDP growth rates. In order to predict GDP growth then, economic situation and economic development strategy have always been used.In this proposed system we plan to implement a system that will help in GDP prediction. By manually it is very hard and time consuming work to analyze data of whole country’s economical progress based on total production in country and investments. Machine Learning technology can help in this work and can give very high level output.Gross Domestic Product (GDP) is an overall estimate of the size of an economy, in terms of total productive output. As such, it is of great importance to policy makers and central banks to know its trend and foresee possible changes. This facilitates accurate assessment of the future state of the economy – whether it be heading toward expansion or contraction – such that preemptive actions can be taken as appropriate. Reliable forecasting of GDP is a very important tool in the macro- economics toolbox. Unfortunately, national economies are profoundly complex and it is not trivial to model them accurately, let alone predict their behavior. Like weather forecasts, GDP forecasts are inherently uncertain and inevitably short-term.

Keywords: Classification, Feature Extraction,GDP, Machine Learning, Economic Indicators,per capita GDP.