Enterprise AI in the Cloud: A Practical Guide to Deploying End-To-End Machine Learning and Chatgpt Solutions

Jay, Rabi

  • 出版商: Wiley
  • 出版日期: 2024-01-11
  • 定價: $2,100
  • 售價: 9.5$1,995
  • 語言: 英文
  • 頁數: 384
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1394213050
  • ISBN-13: 9781394213054
  • 相關分類: ChatGPT人工智慧Machine Learning
  • 立即出貨 (庫存 < 3)


Embrace emerging AI trends and integrate your operations with cutting-edge solutions

Enterprise AI in the Cloud: A Practical Guide to Deploying End-to-End Machine Learning Solutions is a helpful resource for professionals and companies who want to bring new AI technologies like generative AI and machine learning (ML) into their suite of cloud-based solutions. If you want to set up AI platforms in the cloud quickly and confidently and drive your business forward with the power of AI, this book is the ultimate go-to guide. The author shows you how to start an enterprise-wide AI transformation effort, taking you all the way through to implementation, with clearly defined processes, numerous examples, and hands-on exercises.

This book gives you expert guidance on selecting the ideal cloud platform and integrating it with your existing apps and systems. You'll also discover best practices on optimizing cloud infrastructure for scalability and automation. Review questions and answers at the end of every chapter help you assess your understanding of the concepts. Enterprise AI in the Cloud allows you to:

  • Discover a comprehensive approach to implementing corporate AI systems in the cloud and at scale, using an AI-First strategy to drive innovation
  • Learn from emerging AI/ML use cases, such as ChatGPT, VR/AR, blockchain, metaverse, hyper-automation, generative AI, transformer models, Keras, TensorFlow in the cloud, and quantum machine learning
  • Understand the machine learning lifecycle, from framing problems to deploying models and beyond, leveraging the full power of Azure, AWS, and Google cloud platforms
  • Get practical advice on identifying potential use cases, developing a winning AI strategy and portfolio, and driving an innovation culture

Whether you're a beginner or an experienced AI or MLOps (ML Operations) engineer, this comprehensive resource empowers you to confidently build and use AI models in production, bridging the gap between proof-of-concept projects and real-world AI deployments. This book is a must-read for anyone seeking to accelerate AI transformation across their enterprise.





- 探索在雲端和大規模情況下實施企業級人工智慧系統的全面方法,使用以人工智慧為先的策略推動創新
- 從新興的人工智慧/機器學習應用案例中學習,例如ChatGPT、VR/AR、區塊鏈、元宇宙、超自動化、生成式人工智慧、轉換器模型、Keras、雲端中的TensorFlow和量子機器學習
- 了解機器學習的生命周期,從問題定義到模型部署以及更多,充分利用Azure、AWS和Google雲端平台的強大功能
- 獲得有關識別潛在應用案例、制定成功的人工智慧策略和組合,以及推動創新文化的實用建議