Smart Agriculture Using TinyML-managed System – ML/Data Pipeline Contributor
Aws SagemakerImageClassification
Developed and implemented a Smart Agriculture ML model that predicts crop yield based on real-time climate and image data. Managed and prepared data pipelines, integrating IoT sensor streams and image data for machine learning tasks. Trained Convolutional Neural Network (CNN) models using historical and live datasets for predictive analytics.
• Processed and labeled climate and crop image data for model training
• Conducted data quality checks and ensured accurate data annotation for environmental analysis
• Utilized AWS S3 and EC2 instances for data storage and model training workflows
• Optimized data labeling protocols to enhance predictive model accuracy
Developed and implemented a Smart Agriculture ML model that predicts crop yield based on real-time climate and image data. Managed and prepared data pipelines, integrating IoT sensor streams and image data for machine learning tasks. Trained Convolutional Neural Network (CNN) models using historical and live datasets for predictive analytics. • Processed and labeled climate and crop image data for model training • Conducted data quality checks and ensured accurate data annotation for environmental analysis • Utilized AWS S3 and EC2 instances for data storage and model training workflows • Optimized data labeling protocols to enhance predictive model accuracy
Not specified