The idea of a system that can learn from data, identify patterns and make decisions with minimal human intervention is exciting. Deep learning, a type of machine learning that uses neural networks is quickly becoming an effective tool to solve many different computing problems from object classification to recommendation systems. However, getting trained neural networks to be deployed in applications and services can pose challenges for infrastructure managers. Challenges like multiple frameworks, underutilized infrastructure and lack of standard implementations can even cause AI projects to fail. In this blog, we will explore how to navigate these challenges and deploy deep learning models in production in data center or cloud.