Deploying deep learning models with docker and kubernetes

Deploying deep learning models with docker and kubernetes how to#
Deploying deep learning models with docker and kubernetes software#

Keras is the most popular Deep Learning framework that allows Data Scientists to build and validate models on image data.

Deploying deep learning models with docker and kubernetes software#

This is an Open Source project that tries to bridge the gap between Data Scientists and Software Developers. Keras to Kubernetes: The Journey of a Machine Learning Model to ProductionД¬hapter 1: BigData & Artificial IntelligenceД¬hapter 6: Cutting-Edge Deep Learning ProjectsД¬hapter 7: AI in the Modern Software WorldД¬hapter 8: Deploying AI Models as a MicroserviceД¬hapter 9: Machine Learning Development LifecycleД¬hapter 10: A Platform for Machine Learning Below is the table of contents for the book and supported code from the book for your reference. If youвЂ™re ready to learn about one of the most popular DL frameworks and build production applications with it, youвЂ™ve come to the right place. Understand the ML model development lifecycle and deployment to production Reuse examples as-is to deploy your models Learn to uses Keras and Kubernetes to deploy Machine Learning modelsДiscover new ways to collect and manage your image and text data with Machine Learning You will understand the different practical steps involved in real-world ML implementations which go beyond the algorithms.

Deploying deep learning models with docker and kubernetes how to#

You will then take that trained model and package it as a web application container before learning how to deploy this model at scale on a Kubernetes cluster. Keras to Kubernetes: The Journey of a Machine Learning Model to Production takes you through real-world examples of building DL models in Keras for recognizing product logos in images and extracting sentiment from text. DL has many layers of learning and can extract patterns from unstructured data like images, video, audio, etc. ML is all about learning relationships from labeled (Supervised) or unlabeled data (Unsupervised). Within AI, weвЂ™re seeing a particular growth in Machine Learning (ML) and Deep Learning (DL) applications. AI is becoming the new electricity and is touching every industry from retail to manufacturing to healthcare to entertainment. We have seen an exponential growth in the use of Artificial Intelligence (AI) over last few years. Keras to Kubernetes: The Journey of a Machine Learning Model to Production by Dattaraj Jagdish Rao - Book releasing April 2019