• Vaidehi Nimje
• Aboli Kulkarni
• Prajakta Kulkarni
• Ishwari Mahajan
• Geetha Chillarge

The literacy rate is one of the strategic indicators of a country’s economic condition as improved literacy rate leads to augmentation of a country’s human capital. Study, analysis and forecast of various features affecting a country’s literacy has to be carried out to plan improvements in education system so as to increase literacy rate. In this paper, we aim to review the methods to study the trends and patterns in literacy rates over the years, predict the literacy rates based on the available enrollment and population data and present the recommendations to improve the literacy rates. The proposed machine learning model will have to analyze the statistics of literacy based upon multiple factors like Gender, Population, Social classes and categories, Religious communities, Location (urban/rural) and enrollment and dropout rates, etc. It will then give a detailed insight into the trends in literacy in every discipline mentioned above, in the form of visual interactive interpretations (graphs and charts) and perform prescriptive analytics for a targeted region.

Literacy rate, predictive analysis, prescriptive analysis, data analytics, visualization, machine learning.

"Analysis and Forecast Of Literacy Rates in India", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 12, page no.454-458, December-2018, Available :http://www.jetir.org/papers/JETIR1812965.pdf

"Analysis and Forecast Of Literacy Rates in India", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 12, page no. pp454-458, December-2018, Available at : http://www.jetir.org/papers/JETIR1812965.pdf