Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.
Please read the tutorial at this link: https://ebookbell.com/faq
We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.
For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.
EbookBell Team
5.0
28 reviewsEnterprise 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 of
AI-First Strategy: Adopt a comprehensive approach to implementing corporate AI systems in the cloud and at scale, using an AI-First strategy to drive innovation
State-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 learning
Platform Scalability and MLOps (ML Operations): Select the ideal cloud platform and adopt best practices on optimizing cloud infrastructure for scalability and automation
AWS, 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 platforms
AI-Driven Innovation Excellence: Get practical advice on identifying potential use cases, developing a winning AI strategy and portfolio, and driving an innovation culture
Ethical and Trustworthy AI Mastery: Implement Responsible AI by avoiding common risks while maintaining transparency and ethics
Scaling AI
…
