Intermediate
Azure Data Science with Microsoft Fabric
Fabric architecture, data prep, AutoML training, experiment tracking, batch prediction and semantic links.
Microsoft Fabric is an end-to-end unified platform for data science. It brings together all the necessary tools, from storage to artificial intelligence, including integration, machine learning, and BI.
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What's inside
24 sections- 1 Table of Contents
- 2 Introduction and Overview
- 3 Microsoft Fabric Architecture
- 4 Advantages and Challenges of Fabric for Data Science
- 5 Microsoft Fabric Capabilities
- 6 Data Science Lifecycle with Fabric
- 7 Comparison with Other Platforms
- 8 Ideal Use Cases
- 9 Demo: Configuring the MS Fabric Environment
- 10 Data Preparation and Transformation
- 11 Model Training: Manual vs AutoML
- 12 Experiment Tracking
- 13 Batch Predictions with the PREDICT Function
- 14 Distributed Computing for Machine Learning
- 15 Semantic Links: Connecting Data and BI
- 16 Azure AI Tools Integration
- 17 Deriving Insights with AI Techniques
- 18 NLP and Text Analytics with Fabric
- 19 AI Skills in Microsoft Fabric
- 20 Lineage Tracking: Reproducibility and Transparency
- 21 Disaster Recovery Plan for ML Projects
- 22 Security and Access Control for ML Assets
- 23 Compliance and Security Best Practices
- 24 Appendix — Key Concepts Summary
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