Mastering Azure Machine Learning
Execute large-scale end-to-end machine learning with Azure
MACreated by Christoph Körner, Marcel Alsdorf
Explore how to manage the full machine learning lifecycle using Azure Machine Learning. Develop skills in data preparation, model training, and deployment with real-world cloud tools. Gain hands-on experience building scalable, production-ready ML solutions.
Packt | May 2022 | 624 min
What You Will Learn
You will start by setting up your Azure Machine Learning workspace and preparing datasets for analysis. As you progress, you will train a variety of models, from traditional algorithms to deep neural networks, and learn to deploy them for both batch and real-time scenarios. The final sections guide you in automating and managing your ML workflows using MLOps principles.
Key Features
- Set up and manage Azure ML workspaces for streamlined project workflows
- Build, train, and deploy advanced ML models using cloud-based infrastructure
- Automate and monitor ML pipelines with MLOps best practices
Target Audience
Designed for machine learning engineers, data scientists, and developers with a working knowledge of Python and ML concepts. Ideal if you want to use Azure to manage datasets, run experiments, and deploy robust machine learning solutions at scale. If your goal is to build or improve enterprise-grade ML infrastructure, you'll find practical guidance throughout.
