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Data Science with .NET and Polyglot Notebooks

You're reading from   Data Science with .NET and Polyglot Notebooks Programmer's guide to data science using ML.NET, OpenAI, and Semantic Kernel

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Product type Paperback
Published in Aug 2024
Publisher Packt
ISBN-13 9781835882962
Length 404 pages
Edition 1st Edition
Languages
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Author (1):
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Matt Eland Matt Eland
Author Profile Icon Matt Eland
Matt Eland
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Table of Contents (22) Chapters Close

Preface 1. Part 1: Data Analysis in Polyglot Notebooks
2. Chapter 1: Data Science, Notebooks, and Kernels FREE CHAPTER 3. Chapter 2: Exploring Polyglot Notebooks 4. Chapter 3: Getting Data and Code into Your Notebooks 5. Chapter 4: Working with Tabular Data and DataFrames 6. Chapter 5: Visualizing Data 7. Chapter 6: Variable Correlations 8. Part 2: Machine Learning with Polyglot Notebooks and ML.NET
9. Chapter 7: Classification Experiments with ML.NET AutoML 10. Chapter 8: Regression Experiments with ML.NET AutoML 11. Chapter 9: Beyond AutoML: Pipelines, Trainers, and Transforms 12. Chapter 10: Deploying Machine Learning Models 13. Part 3: Exploring Generative AI with Polyglot Notebooks
14. Chapter 11: Generative AI in Polyglot Notebooks 15. Chapter 12: AI Orchestration with Semantic Kernel 16. Part 4: Polyglot Notebooks in the Enterprise
17. Chapter 13: Enriching Documentation with Mermaid Diagrams 18. Chapter 14: Extending Polyglot Notebooks 19. Chapter 15: Adopting and Deploying Polyglot Notebooks 20. Index 21. Other Books You May Enjoy

Handling complex requests with planners

As we saw in the last section, the ability of Semantic Kernel to perform function calling by automatically invoking our functions can lead to powerful results.

However, function calling isn’t always enough.

If you have complex scenarios involving many different plugins and sources of data, the built-in function-calling capabilities may not perform adequately to meet your needs – or you may desire greater visibility into how different functions are chained together to generate your result.

Microsoft has an experimental Microsoft.SemanticKernel.Planners.OpenAI NuGet package that introduces a pair of automated planners to help with more complex tasks.

These planners, FunctionCallingStepwisePlanner and HandlebarsPlanner, may perform better with more complex tasks.

We’ll see how a planner works by showing FunctionCallingStepwisePlanner in action:

#r "nuget:Microsoft.SemanticKernel.Planners.OpenAI,1.16.0...
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