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(Ebook) Enterprise AI in the Cloud: A Practical Guide to Deploying End-to-End Machine Learning and ChatGPT Solutions (Tech Today) by Jay, Rabi ISBN 9781394213054, 1394213050

  • SKU: EBN-54845836
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Instant download (eBook) Enterprise AI in the Cloud: A Practical Guide to Deploying End-to-End Machine Learning and ChatGPT Solutions (Tech Today) after payment.
Authors:Jay, Rabi
Pages:528 pages.
Year:2024
Editon:1
Publisher:Wiley
Language:english
File Size:23.16 MB
Format:pdf
ISBNS:9781394213054, 1394213050
Categories: Ebooks

Product desciption

(Ebook) Enterprise AI in the Cloud: A Practical Guide to Deploying End-to-End Machine Learning and ChatGPT Solutions (Tech Today) by Jay, Rabi ISBN 9781394213054, 1394213050

Embrace emerging AI trends and integrate your operations with cutting-edge solutionsEnterprise AI in the Cloud: A Practical Guide to Deploying End-to-End Machine Learning and ChatGPT Solutions is an indispensable resource for professionals and companies who want to bring new AI technologies like generative AI, ChatGPT, 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. You'll also discover best practices on optimizing cloud infrastructure for scalability and automation.Enterprise AI in the Cloudhelps you gain a solid understanding ofAI-First Strategy: Adopt a comprehensive approach to implementing corporate AI systems in the cloud and at scale, using an AI-First strategy to drive innovationState-of-the-Art Use Cases: 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 learningPlatform Scalability and MLOps (ML Operations): Select the ideal cloud platform and adopt best practices on optimizing cloud infrastructure for scalability and automationAWS, Azure, Google ML: Understand the machine learning lifecycle, from framing problems to deploying models and beyond, leveraging the full power of Azure, AWS, and Google Cloud platformsAI-Driven Innovation Excellence: Get practical advice on identifying potential use cases, developing a winning AI strategy and portfolio, and driving an innovation cultureEthical and Trustworthy AI Mastery: Implement Responsible AI by avoiding common risks while maintaining transparency and ethicsScaling AI…
*Free conversion of into popular formats such as PDF, DOCX, DOC, AZW, EPUB, and MOBI after payment.

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