• Anuradha chopade
• Aastha doshi
• Sonali bodekar

Abstract—Agriculture is India’s prime occupation. The majority of people in the rural and urban areas depend upon this sector directly or indirectly. Agriculture and its components contribute to approximately 20% of India’s GDP in 2020-21. Increasing population, increasing average income, and globalization effects in India will increase demand for quantity, quality and nutritious variety of food. There is immense pressure on farmers to keep up with this demand and supply chain. Even though the technology is upgrading enormously, the rural areas are still using traditional methods of agriculture. Therefore, to accelerate the production process our paper focuses on the prediction of various aspects of agriculture with the help of Machine Learning algorithms and Data Analytics. In this study, we have considered four aspects i.e. Rainfall, Crop production, soil and weather undergoing an ensemble learning algorithm for predictions. This will lead to better yield with minimum usage of resources.

—Machine learning, big data analysis, predic- tions,ensemble learning algorithm,Random Forest Regressor.

"Predictive agricultural using data anlysis and machine learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 6, page no.c15-c18, June-2021, Available :http://www.jetir.org/papers/JETIR2106272.pdf

"Predictive agricultural using data anlysis and machine learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 6, page no. ppc15-c18, June-2021, Available at : http://www.jetir.org/papers/JETIR2106272.pdf