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Proposer
Esraa Khatab
Title
Crop Yield Prediction Using Machine Learning
Goal
Description
This project aims to develop a machine learning model that can accurately predict crop yields based on environmental and agricultural data. With the increasing demand for food and the challenges posed by climate change, predictive analytics in agriculture can help farmers and policymakers make informed decisions to optimize production.
Resources
Background
Url
Difficulty Level
Moderate
Ethical Approval
None
Number Of Students
0
Supervisor
Esraa Khatab
Keywords
precision agriculture, data preprocessing, agricultural data analytics, machine learning
Degrees
Bachelor of Science in Computer Science
Bachelor of Science in Information Systems
Master of Science in Artificial Intelligence
Bachelor of Science in Computing Science
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