Data Science with .NET and Polyglot Notebooks
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Data Science with .NET and Polyglot Notebooks

Programmer's guide to data science using ML.NET, OpenAI, and Semantic Kernel

About the Book

As the fields of data science, machine learning, and artificial intelligence rapidly evolve, .NET developers are eager to leverage their expertise to dive into these exciting domains but are often unsure of how to do so. Data Science in .NET with Polyglot Notebooks is the practical guide you need to seamlessly bring your .NET skills into the world of analytics and AI.

With Microsoft’s .NET platform now robustly supporting machine learning and AI tasks, the introduction of tools such as .NET Interactive kernels and Polyglot Notebooks has opened up a world of possibilities for .NET developers. This book empowers you to harness the full potential of these cutting-edge technologies, guiding you through hands-on experiments that illustrate key concepts and principles. Through a series of interactive notebooks, you’ll not only master technical processes but also discover how to integrate these new skills into your current role or pivot to exciting opportunities in the data science field.

By the end of the book, you’ll have acquired the necessary knowledge and confidence to apply cutting-edge data science techniques and deliver impactful solutions within the .NET ecosystem.

About the Author

Packt Publishing Ltd
Packt Publishing Ltd

Packt Publishing are an established global technical learning content provider, founded in Birmingham, UK with over twenty years’ experience in delivering premium rich content from ground-breaking authors on a wide range of emerging and popular technologies. Our titles have global relevance our multimedia portfolio includes over 9,000 books, e-books, audiobooks and video courses. www.packtpub.com

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

About the Publisher

This book is published on Leanpub by Packt Publishing Ltd

Packt Publishing are an established global technical learning content provider, founded in Birmingham, UK with over twenty years’ experience in delivering premium rich content from ground-breaking authors on a wide range of emerging and popular technologies. Our titles have global relevance our multimedia portfolio includes over 9,000 books, e-books, audiobooks and video courses. www.packtpub.com

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