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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

Generative AI in Polyglot Notebooks

Over Part 1 and Part 2 of this book, we covered data analytics and data science workflows and showed how data can produce insight, guide decision-making, and even help you train predictive models.

This chapter switches direction and covers a specific branch of artificial intelligence (AI) that has erupted in popularity and capabilities in recent years – generative AI.

While generative AI is not unique to Polyglot Notebooks, the notebook environment can make inspecting complex result objects easier.

In this chapter, we’ll use our prowess with Polyglot Notebooks to connect to and interact with generative AI models, see how Polyglot Notebooks provides an ideal sandbox to experiment with generative AI, and explore complex response objects returned by various APIs.

In this chapter, we’ll cover the following topics:

  • Understanding Generative AI
  • Deploying generative AI models on Azure
  • Connecting to an Azure...
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