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

Eland, Matt

  • 出版商: Packt Publishing
  • 出版日期: 2024-08-30
  • 售價: $1,920
  • 貴賓價: 9.5$1,824
  • 語言: 英文
  • 頁數: 404
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 183588296X
  • ISBN-13: 9781835882962
  • 相關分類: .NETData Science
  • 海外代購書籍(需單獨結帳)

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商品描述

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 PowerShell

Key Features:

- Conduct a full range of data science experiments with clear explanations from start to finish

- Learn key concepts in data analytics, machine learning, and AI and apply them to solve real-world problems

- Access all of the code online as a notebook and interactive GitHub Codespace

- Purchase of the print or Kindle book includes a free PDF eBook

Book Description:

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.

What You Will Learn:

- Load, analyze, and transform data using DataFrames, data visualization, and descriptive statistics

- Train machine learning models with ML.NET for classification and regression tasks

- Customize ML.NET model training pipelines with AutoML, transforms, and model trainers

- Apply best practices for deploying models and monitoring their performance

- Connect to generative AI models using Polyglot Notebooks

- Chain together complex AI tasks with AI orchestration, RAG, and Semantic Kernel

- Create interactive online documentation with Mermaid charts and GitHub Codespaces

Who this book is for:

This 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 ML.NET and Semantic kernel and extend their .NET skills to data science, machine learning, and Generative AI Workflows.

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 ML.NET AutoML

- Regression Experiments with ML.NET 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

商品描述(中文翻譯)

擴展您的技能組合,學習如何在 .NET Interactive 筆記本中使用多種語言(包括 C#、F#、SQL 和 PowerShell)進行數據科學、機器學習和生成式 AI 實驗。

主要特點:
- 進行全範圍的數據科學實驗,從頭到尾提供清晰的解釋
- 學習數據分析、機器學習和 AI 的關鍵概念,並應用於解決現實世界的問題
- 在線訪問所有代碼,作為筆記本和互動式 GitHub Codespace
- 購買印刷版或 Kindle 書籍包括免費 PDF 電子書

書籍描述:
隨著數據科學、機器學習和人工智慧領域的快速發展,.NET 開發人員渴望利用他們的專業知識進入這些令人興奮的領域,但往往不確定如何著手。《Data Science in .NET with Polyglot Notebooks》是您無縫將 .NET 技能帶入分析和 AI 世界所需的實用指南。

隨著微軟的 .NET 平台現在強有力地支持機器學習和 AI 任務,.NET Interactive 核心和 Polyglot Notebooks 等工具的引入為 .NET 開發人員開啟了無限可能。本書使您能夠充分利用這些尖端技術,通過實踐實驗指導您理解關鍵概念和原則。通過一系列互動式筆記本,您不僅能掌握技術流程,還能發現如何將這些新技能整合到當前角色中,或轉向數據科學領域的激動人心的機會。

在書籍結束時,您將獲得必要的知識和信心,能夠應用尖端的數據科學技術,並在 .NET 生態系統中提供有影響力的解決方案。

您將學到的內容:
- 使用 DataFrames、數據可視化和描述性統計來加載、分析和轉換數據
- 使用 ML.NET 訓練機器學習模型以進行分類和回歸任務
- 使用 AutoML、自定義轉換和模型訓練器來定制 ML.NET 模型訓練管道
- 應用最佳實踐來部署模型並監控其性能
- 使用 Polyglot Notebooks 連接到生成式 AI 模型
- 通過 AI 編排、RAG 和 Semantic Kernel 將複雜的 AI 任務鏈接在一起
- 使用 Mermaid 圖表和 GitHub Codespaces 創建互動式在線文檔

本書適合對象:
本書適合有經驗的 C# 或 F# 開發人員,他們希望在利用 .NET 專業知識的同時轉型進入數據科學和機器學習。對於那些希望學習 ML.NET 和 Semantic Kernel,並將其 .NET 技能擴展到數據科學、機器學習和生成式 AI 工作流程的人來說,這是理想的選擇。

目錄:
- 數據科學、筆記本和核心
- 探索 Polyglot Notebooks
- 將數據和代碼導入您的筆記本
- 使用表格數據和 DataFrames
- 數據可視化
- 變數相關性
- 使用 ML.NET AutoML 進行分類實驗
- 使用 ML.NET AutoML 進行回歸實驗
- 超越 AutoML:管道、訓練器和轉換
- 部署機器學習模型
- 在 Polyglot Notebooks 中的生成式 AI
- 使用 Semantic Kernel 進行 AI 編排
- 使用 Mermaid 圖表豐富文檔
- 擴展 Polyglot Notebooks
- 採用和部署 Polyglot Notebooks