Leveraging Machine Learning to Predict Crop Yields for Sustainable Agriculture Development

1. Introduction 1.1 Background and Motivation 1.2 Objectives of the Study 1.3 Scope and Limitations 1.4 Structure of the Paper 2. Literature Review 2.1 Overview of Machine Learning in Agriculture 2.2 Techniques for Crop Yield Prediction 2.3 Sustainability in Agricultural Practices 3. Methodology 3.1 Data Collection and Sources 3.2 Selection of Machine Learning Models 3.3 Model Training and Validation 4. Data Analysis 4.1 Preprocessing of Agricultural Data 4.2 Feature Selection Techniques 4.3 Exploratory Data Analysis 5. Model Development 5.1 Implementation of Regression Models 5.2 Evaluation Metrics for Model Performance 5.3 Model Optimization Strategies 6. Results 6.1 Predictive Accuracy of Models 6.2 Comparative Analysis of Model Performance 6.3 Interpretation of Results 7. Discussion 7.1 Implications for Sustainable Agriculture 7.2 Impact of Accurate Yield Predictions 7.3 Limitations and Future Research 8. Conclusion 8.1 Summary of Key Findings 8.2 Recommendations for Practice 8.3 Future Directions in Research