Table of Contents
- Understanding the End-to-End Machine Learning Process
- Choosing the Right Machine Learning Service in Azure
- Preparing the Azure Machine Learning Workspace
- Ingesting Data and Managing Datasets
- Performing Data Analysis and Visualization
- Feature Engineering and Labeling
- Advanced Feature Extraction with NLP
- Azure Machine Learning Pipelines
- Building ML Models Using Azure Machine Learning
- Training Deep Neural Networks on Azure
- Hyperparameter Tuning and Automated Machine Learning
- Distributed Machine Learning on Azure
- Building a Recommendation Engine in Azure
- Model Deployment, Endpoints, and Operations
- Model Interoperability, Hardware Optimization, and Integrations
- Bringing Models into Production with MLOps
- Preparing for a Successful ML Journey

