NEX AI: Deployment of Machine Learning Pipelines using Google Cloud ML Engine and AWS SageMaker

NASA Earth Exchange (NEX) research focuses on analysis and visualization of modeling Earth data in large-scale computing. The massive datasets from NEX require high-intensive data processing and include remote-sensing land, atmosphere, hydrology, and other complex earth sciences metadata. With supercomputers (ie Pleiades) to accelerate research in Earth systems science and global change, we found this process can improve upon better infrastructures and automated pipelines. Machine Learning (ML) pipelines help package algorithms, libraries, and additional code dependencies to go through the stages from labeling data to predictions, and from training and deploying a model to full-scale application. NEX-AI is an in-house ML pipeline that allows NEX researchers to select pre-configured algorithms and submit complex data easily. As machine learning rises rapidly in the global market," as a service" …