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Data Science with .NET and Polyglot Notebooks

Data Science with .NET and Polyglot Notebooks

By : Matt Eland
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Data Science with .NET and Polyglot Notebooks

Data Science with .NET and Polyglot Notebooks

By: Matt Eland

Overview of this 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.
Table of Contents (22 chapters)
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1
Part 1: Data Analysis in Polyglot Notebooks
8
Part 2: Machine Learning with Polyglot Notebooks and ML.NET
13
Part 3: Exploring Generative AI with Polyglot Notebooks
16
Part 4: Polyglot Notebooks in the Enterprise

Calling multiple functions using plugins

Semantic Kernel accomplishes AI orchestration by allowing you to integrate plugins into the kernel.

A Semantic Kernel plugin is a collection of one or more KernelFunction objects that can be discovered and invoked by the kernel in response to a specific input. This lets the kernel choose which function or functions might be relevant to responding to a specific prompt such as a message from a user.

Plugins can be defined by inheriting from the KernelPlugin class or via one of the simpler import methods built into kernel instances.

We’ll take the latter approach because we want to create a simple plugin that combines some of the various functions we’ve created so far:

KernelPlugin plugin =
  kernel.ImportPluginFromFunctions("FootballPlugin",
    "A collection of functions related to football",
    functions: [coach, timeFunc, teamInfoFunc, searchFunc...
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Tech Concepts
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Programming languages
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