Leveraging Machine Learning for Sustainable Agriculture

The book makes a significant contribution to the community by presenting a cutting-edge fertilizer recommendation model. This model holds the potential to diminish land pollution and bolster sustainability in agriculture practices. Considering the criticality of predicting crop yield for survival in the sector, the book further compares existing machine learning algorithms. The findings reveal that the proposed models outperform the existing ones, making them highly suitable for adoption by various organization to accurately predict crop yields.

Autorentext

Dr. Shivani Kale, Ph.D., is a distinguished expert in the field of Computer Science with a passion for leveraging cutting-edge technologies to address real-world challenges. With her strong academic background and years of research experience, she has become a driving force in the application of machine learning for agriculture sustainability.