Data Science with .NET and Polyglot Notebooks: Programmer's guide to data scienc

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Data Science with .NET and Polyglot Notebooks by Matt Eland

Expand your skillset by learning how to perform data science, machine learning, and generative AI experiments in .NET Interactive notebooks using a variety of languages, including C#, F#, SQL, and PowerShellKey FeaturesConduct a full range of data science experiments with clear explanations from start to finishLearn key concepts in data analytics, machine learning, and AI and apply them to solve real-world problemsAccess all of the code online as a notebook and interactive GitHub CodespacePurchase of the print or Kindle book includes a free PDF eBookBook DescriptionAs 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 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 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 you will learnLoad, analyze, and transform data using DataFrames, data visualization, and descriptive statisticsTrain machine learning models with for classification and regression tasksCustomize model training pipelines with AutoML, transforms, and model trainersApply best practices for deploying models and monitoring their performanceConnect to generative AI models using Polyglot NotebooksChain together complex AI tasks with AI orchestration, RAG, and Semantic KernelCreate interactive online documentation with Mermaid charts and GitHub CodespacesWho this book is forThis book is for experienced C# or F# developers who want to transition into data science and machine learning while leveraging their .NET expertise. It's ideal for those looking to learn and Semantic kernel and extend their .NET skills to data science, machine learning, and Generative AI Workflows.

FORMAT
Paperback CONDITION
Brand New Table of Contents

Table of Contents

Data Science, Notebooks, and Kernels

Exploring Polyglot Notebooks

Getting Data and Code into Your Notebooks

Working with Tabular Data and DataFrames

Visualizing Data

Variable Correlations

Classification Experiments with AutoML

Regression Experiments with AutoML

Beyond AutoML: Pipelines, Trainers, and Transforms

Deploying Machine Learning Models

Generative AI in Polyglot Notebooks

AI Orchestration with Semantic Kernel

Enriching Documentation with Mermaid Diagrams

Extending Polyglot Notebooks

Adopting and Deploying Polyglot Notebooks

Details ISBN183588296X Author Matt Eland Pages 404 Publisher Packt Publishing Limited Year 2024 ISBN-13 9781835882962 Format Paperback Publication Date 2024-08-30 Imprint Packt Publishing Limited Subtitle Programmer's guide to data science using ML.NET, OpenAI, and Semantic Kernel Place of Publication Birmingham Country of Publication United Kingdom UK Release Date 2024-08-30 Country of Origin US Product Class Description Computing: Professional & Programming Audience Professional & Vocational
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