Abstract:
India's agriculture sector serves a significant role. It is essential to update ideas and methods in order to
maintain standards in order to keep up with global warming and other demographic and materialistic issues that keep
piling up. Being the top producer of a range of crops throughout the world has made it necessary to update ideas and
methods in recent years. Predictive systems are a crucial instrument for management and decision-making in every
productive industry. In agriculture, it is particularly valuable to have advance knowledge of a farm's profit potential.
Consequently, depending on the time of year when this information is available, crucial decisions can be made that
impact the farm's financial stability. The objective of this study is to develop a model for predicting Seed and pertinent
characteristics in advance that is easily accessible and usable by farmers through a web application. This includes
more sophisticated methods that have been derived from machine learning technologies and algorithms such as
generative models and random classifiers. The fundamental motivation behind this work is to facilitate prediction
using a machine learning model. The Seed suggestion model provides assistance in resolving a variety of innovative
and frequently disregarded challenges that the younger generation of farmers is currently facing. Research on yield
estimation in agriculture is beneficial for farmers as it helps them minimize crop loss and maximize profits by
obtaining the best prices for their increased yield production. Prioritizing crop-sowing techniques in agricultural
research also improves the well-being of the land, farmers, and others.