ENHANCING AGRICULTURAL PRODUCTIVITY THROUGH DATA SCIENCE AND MACHINE LEARNING
Keywords:
Optimization, Data Analysis Agriculture Machine Learning, Data Science, Modeling, Crop Productivity.Abstract
The research utilizes methods such as data analysis, predictive modeling, and machine learning algorithms to examine agricultural data and generate actionable insights. This study focuses on optimizing agricultural practices through the application of data science and machine learning techniques. Agriculture plays a crucial role in ensuring global food security and economic stability, making its efficiency and sustainability a priority. Key objectives include enhancing crop productivity, reducing resource wastage, and improving overall farm management. The findings aim to support informed decision-making for farmers, policymakers, and stakeholders. Ultimately, this work contributes to the advancement of sustainable agriculture by promoting efficient resource utilization and increasing profitability
