Crop yield prediction using machine learning and deep learning
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BRAC University
Citation
Abstract
Bangladesh is an agrarian country. Though, a substantial portion of our economy
and workforce depends directly or indirectly on agriculture. However, due to climate
change, floods, insufficient incentives, and less grist our farmers are getting demotivated
in farming. As a result, more and more farmers are leaving the agriculture
sector every year and this can cause devastating effects for Bangladesh. Moreover,
there is little or no research on improving Bangladesh agriculture using cutting-edge
machine learning techniques. So, this research works on Crop yield prediction Using
Machine learning and deep learning. This work explores the different state-of-the-art
machine learning and deep learning techniques and relevant dataset to develop an
effective Crop yield prediction system for Bangladeshi farmers. So that our farmers
can decide which crop to cultivate for gaining the maximum yield by following our
prediction system.
LC Subject Headings
Description
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 34-35).
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2024.
Includes bibliographical references (pages 34-35).
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2024.
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Thesis