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[Crop Yield Prediction using Machine learning techniques ]
[Crop Yield Prediction using Machine learning techniques ]
(Feb 2022 - Feb 2022 )
Its the prediction of crop yield which is very helpful for the farmers to predict the best yield NaiveBayers of the crops by using Machine learning techniques in which we use NaiveBayers (NB) and K-Nearest Neighbour (KNN) algorithm, It prevents crop failures .
Its the prediction of crop yield which is very helpful for the farmers to predict the best yield NaiveBayers of the crops by using Machine learning techniques in which we use NaiveBayers (NB) and K-Nearest Neighbour (KNN) algorithm, It prevents crop failures .
A description of the above images are a showcasing of the project site portal for farmers.
A description of the above images are a showcasing of the project site portal for farmers.
The above data shown is the machine learning technique with the help of "NAIVE BAYERS" AND KK-NEAREST MAPPING algorithm predicting the perfect yield of crop at right time to ensure farmers with the best crop yield production and preventing crop failures.
Agriculture is the field which helps in economic growth of our country. But this is lacking behind in
using new technologies of machine learning. Hence our farmers should know all the new
technologies of machine learning and other new techniques. These techniques help in getting
maximum yield of crops. Many techniques of machine learning are applied on agriculture to
improve yield rate of crops. These techniques also help in solving problems of agriculture. We can
also get the accuracy of yield by checking for different methods. Hence we can improve the
performance by checking the accuracy between different crops. Sensor technologies are
implemented in many farming sectors. This paper helps in getting maximum yield rate of the crops.
Also helps in selecting proper crop for their selected land and selected season. These techniques
will solve the problems of farmers in agriculture field. This will help in improving the economic
growth of our country.
SPECIAL THANKS :-
Mohammed Abdul Samad
Mohammed Abdul Raqeeb
Asjad Raza
"With the help of my fellow members and me we are very much delightful to deploy our project to the fields of agriculture "
Crop yield Prediction Project.pdfPage updated
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