Crop Prediction and Crop Quantity Suggestion Based on the Characteristics of Agricultural Environment using Machine Learning Techniques

An expanding area of study is agriculture. Agriculture, in particular, depends heavily on soil and environmental factors including temperature, humidity, and rainfall. Crop forecast is also crucial. The choice of the crop to be grown, its development, and its harvesting date could all be controlled by farmers in the past. However, the community of farmers now finds it challenging to carry on as a result of the quick changes in the environment. Therefore, machine learning methods have largely replaced traditional prediction methods in recent years. This work has used a number of these methods to calculate agricultural yield. Efficient feature selection techniques must be used to preprocess the data in order to guarantee that a given machine learning (ML) model operates with a high level of precision.