Ten strategies to implement AI on the Cloud and Edge

The deployment of Machine Learning and Deep Learning algorithms on Edge devices is a complex undertaking. In this post, I list the strategies for deploying AI to Edge devices end-to-end i.e. for the full pipeline covering machine learning (building modules) and deployment (devops) I welcome your comments on additional ideas that could be included. In subsequent posts, I will elaborate these ideas in detail and ultimately, this will a free book on Data Science Central. I will take a use-case based approach i.e. each section would start with a use case. Many IoT applications are simple telemetry applications i.e. data is captured using a single sensor and action is undertaken based on the data. In doing so, the data may be stored or visualised.