Data Science with .NET and Polyglot Notebooks

Table of Contents

1. Data Science, Notebooks, and Kernels
2. Exploring Polyglot Notebooks
3. Getting Data and Code into Your Notebooks
4. Working with Tabular Data and DataFrames
5. Visualizing Data
6. Variable Correlations
7. Classification Experiments with ML.NET AutoML
8. Regression Experiments with ML.NET AutoML
9. Beyond AutoML: Pipelines, Trainers, and Transforms
10. Deploying Machine Learning Models
11. Generative AI in Polyglot Notebooks
12. AI Orchestration with Semantic Kernel
13. Enriching Documentation with Mermaid Diagrams
14. Extending Polyglot Notebooks
15. Adopting and Deploying Polyglot Notebooks