Machine learning shows tremendous potential for increasing process efficiency. But generating real, lasting value requires more than just the best algorithms. To streamline the AI development process, AI operations have emerged as an important theme. It involves pertinent questions like: how do you maintain an up to date data store? How would you update the model features? how do you keep the code running reliably in production? How do you monitor its performance? How do you deploy new versio...
