دانلود کتاب هوش مصنوعی نهایی Snowflake Cortex برای کاربردهای هوش مصنوعی مولد

This book is a comprehensive and practical guide tailored for data scientists, engineers, analysts, data professionals and business leaders seeking to harness the full potential of Generative AI on Snowflake Cortex—Snowflake’s powerful native AI engine. This book delves deep into the capabilities of Cortex, equipping readers with the knowledge and tools needed to design, build, and deploy cutting-edge Generative AI and Machine Learning applications. From foundational concepts to advanced use cases, it provides a structured and hands-on approach to leveraging Snowflake’s unified data cloud platform for modern AI development. Whether you are aiming to enhance productivity through intelligent automation, derive insights from unstructured data, build domain-specific LLMs, implement intelligent document processing, fine-tune models for specific use cases, or orchestrate AI workflows using Snowflake agents, this book serves as your essential companion. It also helps deepen your understanding of realworld industry applications, guiding you on the journey toward AI-driven innovation within the Snowflake ecosystem. This book is organized into 11 comprehensive chapters, listed as follows: Chapter 1. Introduction to AI/ML in the Snowflake Ecosystem: This foundational chapter introduces readers to the world of Artificial Intelligence and Machine Learning, explaining core concepts such as Deep Learning, Natural Language Processing, and Computer Vision. It also presents the evolution of Generative AI and its growing impact across industries. The chapter concludes by exploring Snowflake’s architecture and how it supports scalable AI and ML initiatives through its native tools with a brief overview of Snowpark ML. Chapter 2. Understanding Snowflake Cortex: This chapter provides a deep dive into Snowflake Cortex, outlining its key features and internal components that make AI/ML development more accessible within the Snowflake ecosystem. It compares Cortex with traditional ML pipelines and emphasizes its advantages in terms of speed, scalability, and simplicity. Readers will gain clarity on how Cortex seamlessly integrates into enterprise data workflows. Chapter 3. Overview of Machine Learning Functions: This chapter focuses on the core ML functions natively available in Snowflake, including classification, forecasting, anomaly detection, and extracting top insights. It demonstrates how these functions can be used to address real-world business problems and showcases the convenience of operating ML within a single, governed platform using Cortex and the AI & ML Studio. Chapter 4. Introduction to LLMs, Prompt Engineering, and RAG: This chapter sets the stage for working with Large Language Models (LLMs) by covering their fundamentals, along with techniques such as prompt engineering and Retrieval Augmented Generation (RAG). It explores how embedding-based search and vector databases play a vital role in augmenting LLMs, paving the way for more context-aware and efficient information retrieval. Chapter 5. LLM Functions in Cortex AI: Dedicated to Snowflake Cortex’s LLM capabilities, this chapter highlights how users can seamlessly invoke pre-trained LLMs for summarization, sentiment analysis, translation, and more. It covers usage models, regional availability, and cost considerations, and helps readers understand how LLMs are democratized through Cortex for enterprise-grade use cases. Chapter 6. Fine-Tuning Large Language Models in Cortex: In this chapter, readers learn why and how to finetune LLMs using Snowflake Cortex. It explores various finetuning strategies, from instruction tuning to domainspecific adjustments, and provides an architectural overview of the finetuning process. The chapter also discusses the benefits of personalized AI models and how organizations can achieve them securely within Cortex. Chapter 7. Natural Language Queries to Actionable Insights: This chapter explores Snowflake’s capabilities for turning plain-language questions into data-driven insights. It introduces tools such as Cortex Analyst, Cortex Search, and SQL Copilot, which allow users to interact with structured and unstructured data using natural language. It also discusses the concept of AI agents that orchestrate these interactions behind the scenes. We will also look at the Cortex LLM Playground, an interactive environment within Snowflake for quickly testing large language models using natural language, making it easy to test ideas and validate AI-driven insights without extensive coding. Chapter 8. Unlocking Document Intelligence with Document AI: Here, the book dives into Document AI and the potential it brings for transforming unstructured documents into structured, actionable data. The chapter covers implementation guidance, best practices, and realworld use cases that span industries such as finance, legal, and healthcare. Chapter 9. Implementing Cortex with Security, Governance, and Cost Discipline: This chapter ensures that readers understand the importance of secure and responsible AI practices. It covers security and governance best practices, strategies for cost optimization, and tools for AI observability in Cortex. It is a must-read for those planning to deploy AI at enterprise scale. Chapter 10. Industry Use Cases and Case Studies: Bringing everything together, this chapter presents a wide array of industry-specific use cases implemented with Cortex. These examples—ranging from customer sentiment analysis, predictive maintenance, social media analytics, and student performance analysis illustrate the versatility of Cortex. The fictional company Zentime is used throughout the book as a unifying thread to illustrate and contextualize AI applications. We will conclude by summarizing the key generative AI features within Cortex that enable these diverse and impactful solutions. Chapter 11. Conclusion and Next Steps: The final chapter reflects the journey through Cortex AI, summarizing the key takeaways from each chapter. It also highlights future trends and provides practical next steps for readers to begin or accelerate their AI transformation journey using Snowflake Cortex.