A SURVEY ON THE PREDICTION OF CROP YIELD USING MACHINE LEARNING AND CLOUD COMPUTING

Agriculture is the first major source of livelihood for our country. For now challenges of water scarcity, uncontrolled costs due to service delivery, and climate change uncertainty enables farmers to equip farmers with smart farming. Mostly, low crop yields are due to unpredictable climate change, poor irrigation systems, and depletion. AI Platform Prediction can capture your models to get you guessed at them in the cloud. The process of capturing a saved model is called deployment. The forecasting service controls the infrastructure required to use your model on the scale and makes it available for online guessing applications and collections. This section describes the use of models. Prediction is forecasting the future based on the available data set, Prediction is what someone thinks will happen, Prediction using machine Learning gives us more accurate results based on data that is used for training the model. You can easily host scale and deploy the machine learning models in the cloud and use AI Platform Prediction to infer target values for new data.