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.

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Spis treści

Data Science with .NET and Polyglot Notebooks. Programmer's guide to data science using ML.NET, OpenAI, and Semantic Kernel eBook -- spis treści

• 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