ML Ops topped LinkedIn's Emerging Jobs ranking, with a recorded growth of 9.8 times in five years. Most individuals looking to enter the data industry possess machine learning skills. However, most data scientists are unable to put the models they build into production. As a result, companies are now starting to see a gap between models and production. Most machine learning models built in these companies are not usable, as they do not reach the end-user's hands.

ML Ops topped LinkedIn's Emerging Jobs ranking, with a recorded growth of 9.8 times in five years. Most individuals looking to enter the data industry possess machine learning skills. However, most data scientists are unable to put the models they build into production. As a result, companies are now starting to see a gap between models and production. Most machine learning models built in these companies are not usable, as they do not reach the end-user's hands.

Containerize your Apps with Docker and Kubernetes is an excellent free book from Gabriel N. Schenker In this post, I explain the significance of deploying apps with Docker and Kubernetes and also some of my thinking at the University of Oxford artificial intelligence cloud and edge impleme... course. Chapter 1: What Are Containers and Why Should I Use Them? Containers are the best way to implement a DevOps architecture. This book explains the end-to-end deployment of containers for an Azure environment – including container orchestration through Kubernetes. The book explains the software supply chain and the friction within it – and then presents containers as a means to reduce this friction and add enterprise-grade security on top of it.

As described in the Part 1, I wanted to deploy my Deep Learning model into production. I've shown how to prepare the model for TensorFlow Serving. We exported the GAN model as Protobuf and it is now ready to be hosted. TensorFlow Serving implements a server that processes incoming requests and forwards them to a model. This server could be running somewhere, most probably, at your Cloud provider (such as Amazon AWS, Google Cloud Platform, Microsoft Azure), to be available to the world.