Deploy Machine Learning Models to Production

Microsoft Azure Machine Learning: Explore predictive analytics using step-by-step tutorials and build models to make prediction in a jiffy with a few mouse clicks

Engineering MLOps: Rapidly build, test, and manage production-ready machine learning life cycles at scale on Azure

Getting Started with Amazon SageMaker Studio: Learn to build end-to-end machine learning projects in the SageMaker machine learning IDE

Implementing MLOps in the Enterprise - by Yaron Haviv & Noah Gift (Paperback)

Beginning MLOps with Mlflow: Deploy Models in AWS Sagemaker Google Cloud and Microsoft Azure (Paperback)

Machine Learning in the Cloud: Automate and Scale Machine Learning Pipelines in the Cloud

MLOps: Engineering Machine Learning Systems

Pre-Owned Machine Learning Engineering on AWS: Build scale and secure machine learning systems and MLOps (Paperback) by Joshua Arvin Lat

Practical Automated Machine Learning on Azure: Using Azure Machine Learning to Quickly Build AI Solutions

Deep Learning with Azure: Building and Deploying Artificial Intelligence Solutions on the Microsoft AI Platform

Machine Learning with Microsoft Technologies: Selecting the Right Architecture and Tools for Your Project

Machine Learning Engineering with Python - Second Edition - 2nd Edition by Andrew McMahon (Paperback)

Applied Machine Learning and High-Performance Computing on AWS: Accelerate the development of machine learning applications following architectural best practices

Machine Learning Pipelines: A Comprehensive Guide to Building and Deploying Intelligent Systems

Learn TensorFlow Enterprise: Build, manage, and scale machine learning workloads seamlessly using Google's TensorFlow Enterprise

The Machine Learning Solutions Architect Handbook - Second Edition - by David Ping (Paperback)

The DevOps Engineer's Guide to AI: How to Deploy, Monitor, and Scale AI Applications Using Modern DevOps Practices and Tools

Real-World Machine Learning

"Machine Learning Algorithms and Applications in Engineering | Environmental Engineering

Data Science on the Google Cloud Platform: Implementing End-to-End Real-Time Data Pipelines: From Ingest to Machine Learning [first edition]

Machine Learning Platform Engineering: Build an internal developer platform for ML and AI systems (From Scratch) Tan Wei Hao, Benjamin; Padmanabhan,