Data Science Solutions on Azure: The Rise of Generative AI and Applied AI

Soh, Julian, Singh, Priyanshi

Data Science Solutions on Azure: The Rise of Generative AI and Applied AI
  • 出版商: Apress
  • 出版日期: 2024-12-03
  • 售價: $2,210
  • 貴賓價: 9.5 折 $2,100
  • 語言: 英文
  • 頁數: 280
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 9798868809132
  • ISBN-13: 9798868809132
  • 相關分類: Microsoft Azure、人工智慧、Data Science

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商品描述

This revamped and updated book focuses on the latest in AI technology--Generative AI. It builds on the first edition by moving away from traditional data science into the area of applied AI using the latest breakthroughs in Generative AI.

Based on real-world projects, this edition takes a deep look into new concepts and approaches such as Prompt Engineering, testing and grounding of Large Language Models, fine tuning, and implementing new solution architectures such as Retrieval Augmented Generation (RAG). You will learn about new embedded AI technologies in Search, such as Semantic and Vector Search.

Written with a view on how to implement Generative AI in software, this book contains examples and sample code.

In addition to traditional Data Science experimentation in Azure Machine Learning (AML) that was covered in the first edition, the authors cover new tools such as Azure AI Studio, specifically for testing and experimentation with Generative AI models.

What's New in this Book

  • Provides new concepts, tools, and technologies such as Large and Small Language Models, Semantic Kernel, and Automatic Function Calling
  • Takes a deeper dive into using Azure AI Studio for RAG and Prompt Engineering design
  • Includes new and updated case studies for Azure OpenAI
  • Teaches about Copilots, plugins, and agents

What You'll Learn

  • Get up to date on the important technical aspects of Large Language Models, based on Azure OpenAI as the reference platform
  • Know about the different types of models: GPT3.5 Turbo, GPT4, GPT4o, Codex, DALL-E, and Small Language Models such as Phi-3
  • Develop new skills such as Prompt Engineering and fine tuning of Large/Small Language Models
  • Understand and implement new architectures such as RAG and Automatic Function Calling
  • Understand approaches for implementing Generative AI using LangChain and Semantic Kernel
  • See how real-world projects help you identify great candidates for Applied AI projects, including Large/Small Language Models

商品描述(中文翻譯)

這本經過改版和更新的書籍專注於最新的人工智慧技術——生成式人工智慧。它在第一版的基礎上，從傳統數據科學轉向應用人工智慧，利用生成式人工智慧的最新突破。

基於真實世界的專案，本版深入探討了新的概念和方法，例如提示工程（Prompt Engineering）、大型語言模型的測試和基礎設置、微調，以及實施新的解決方案架構，如檢索增強生成（Retrieval Augmented Generation, RAG）。您將學習到在搜尋中嵌入的人工智慧新技術，例如語義搜尋和向量搜尋。

本書以如何在軟體中實施生成式人工智慧為視角，包含範例和示範程式碼。

除了第一版中涵蓋的傳統數據科學實驗在 Azure Machine Learning (AML) 的內容外，作者還介紹了新的工具，如 Azure AI Studio，專門用於測試和實驗生成式人工智慧模型。

本書的新內容包括：
- 提供新的概念、工具和技術，如大型和小型語言模型、語義核心（Semantic Kernel）和自動函數調用（Automatic Function Calling）
- 更深入地探討如何使用 Azure AI Studio 進行 RAG 和提示工程設計
- 包含針對 Azure OpenAI 的新案例研究
- 教授有關副駕駛（Copilots）、插件和代理的知識

您將學到：
- 了解大型語言模型的重要技術面，並以 Azure OpenAI 作為參考平台
- 知曉不同類型的模型：GPT3.5 Turbo、GPT4、GPT4o、Codex、DALL-E，以及小型語言模型如 Phi-3
- 發展新的技能，如提示工程和大型/小型語言模型的微調
- 理解並實施新的架構，如 RAG 和自動函數調用
- 理解使用 LangChain 和語義核心實施生成式人工智慧的方法
- 了解真實世界專案如何幫助您識別適合應用人工智慧專案的優秀候選者，包括大型/小型語言模型

作者簡介

Julian Soh is a software engineer at Microsoft, focusing on the areas of artificial intelligence and advanced analytics for Independent Software Vendors (ISVs) who develop software solutions based on the Microsoft technology stack. Prior to his current role, Julian worked extensively on major public cloud initiatives, such as SaaS (Microsoft 365), IaaS/PaaS (Microsoft Azure), and hybrid private-public cloud implementations.

Priyanshi Singh is a software engineer and a data scientist by training. She is a data enthusiast by nature specializing in machine learning techniques applied to predictive analytics, computer vision, and natural language processing. She holds a master's degree in Data Science from New York University and is currently a software solutions engineer at Microsoft helping the public sector to transform citizen services with Artificial Intelligence. She also leads a Meetup community based out of New York to help educate public sector employees via hands-on labs and discussions. Apart from her passion for learning new technologies and innovating with AI, she is a sports lover, a great badminton player, and enjoys playing billiards.

作者簡介(中文翻譯)

Julian Soh 是微軟的一名軟體工程師，專注於人工智慧和高級分析領域，為基於微軟技術堆疊開發軟體解決方案的獨立軟體供應商（ISVs）提供支持。在擔任目前職位之前，Julian 曾廣泛參與主要的公共雲計畫，例如 SaaS（Microsoft 365）、IaaS/PaaS（Microsoft Azure）以及混合私有-公共雲實施。

Priyanshi Singh 是一名軟體工程師，並具備數據科學的專業背景。她天生對數據充滿熱情，專精於應用於預測分析、計算機視覺和自然語言處理的機器學習技術。她擁有紐約大學的數據科學碩士學位，目前在微軟擔任軟體解決方案工程師，協助公共部門利用人工智慧轉型市民服務。她還在紐約領導一個 Meetup 社群，幫助公共部門員工通過實作實驗室和討論進行教育。除了對學習新技術和利用 AI 創新的熱情外，她還是一位運動愛好者，是一名出色的羽球選手，並喜歡打撞球。

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