About the Book

About the Book

Mastering RHEL AI: Building and Scaling AI Solutions with Red Hat Enterprise Linux is a comprehensive guide designed to help developers, data scientists, IT professionals, and enterprises unlock the full potential of AI on Red Hat Enterprise Linux (RHEL). This book takes readers through the entire lifecycle of AI development, from understanding the foundational components of RHEL AI to deploying, managing, and scaling AI models in production environments.

Who Should Read This Book?

This book is ideal for:

• AI Developers and Data Scientists: Looking to build and deploy machine learning models at scale using a secure, enterprise-grade platform.
• IT Professionals and System Administrators: Interested in learning how to optimize infrastructure for AI workloads using RHEL AI’s powerful tools and resources.
• Business Leaders and Decision Makers: Seeking to understand the strategic advantages of leveraging RHEL AI to drive innovation and improve decision-making within their organizations.
• AI Enthusiasts and Students: Wanting to learn about cutting-edge AI technologies, including Explainable AI, Edge AI, and Quantum AI, with practical examples and real-world use cases.

What You'll Learn

This book covers a wide range of topics, providing a detailed and practical approach to AI development on RHEL AI. Key areas include:

1. Introduction to RHEL AI: Understand the capabilities of RHEL AI, its core components, and the benefits it offers to enterprise AI projects.
2. Setting Up and Configuring RHEL AI: A step-by-step guide to installing RHEL AI, setting up virtual environments, enabling GPU acceleration, and configuring cloud integration.
3. Advanced AI Features: Explore advanced capabilities like GPU acceleration, cloud-based AI deployments, and security measures for AI workloads.
4. Developing Custom AI Applications: Learn how to build, train, and deploy custom AI models using popular machine learning libraries like TensorFlow, PyTorch, and Scikit-learn, along with integrating third-party tools.
5. Monitoring and Maintaining AI Workloads: Gain insight into using tools like Prometheus and Grafana to monitor and troubleshoot AI systems in real-time.
6. Use Cases and Best Practices: Dive into real-world examples of how RHEL AI is transforming industries such as healthcare, finance, and manufacturing, with practical tips for optimizing performance and ensuring security.
7. Future Trends in AI: Stay ahead of the curve by exploring emerging AI trends such as Explainable AI (XAI), Edge AI, Quantum AI, and the increasing importance of AI governance and ethics.
8. Community and Support: Discover how to engage with the RHEL AI community, access official support channels, and advance your expertise through Red Hat's training and certification programs.

Why RHEL AI?

As artificial intelligence becomes a key driver of innovation across industries, having the right infrastructure in place is essential for successful AI deployments. RHEL AI offers a secure, scalable, and enterprise-ready platform that integrates seamlessly with AI development workflows. Whether you're building AI models on-premises or leveraging the power of the cloud, RHEL AI provides the tools and infrastructure needed to deploy AI solutions with confidence.

In a nutshell

Mastering RHEL AI: Building and Scaling AI Solutions with Red Hat Enterprise Linux is your go-to resource for developing, managing, and optimizing AI models using RHEL AI. Whether you’re just starting your AI journey or you’re looking to refine your skills, this book offers the practical knowledge and expert insights needed to succeed in building AI-driven solutions in today’s fast-evolving technology landscape.

About the Author

Luca Berton

@ansiblepilot

Instagram

Luca Berton is an Ansible Automation Expert who has been working with JPMorgan Chase & Co. and previously worked with the Red Hat Hat Ansible Engineer Team for three years. Published author of the Ansible for VMware by Examples and Ansible for Kubernetes by Examples best-seller of the Ansible By Example(s) practical book series and creator of the Ansible Pilot project. With more than 15 years of experience as a System Administrator, he has strong expertise in Infrastructure Hardening and Automation. Enthusiast of the Open Source supports the community, sharing his knowledge in different events of public access. Geek by nature, Linux by choice, Fedora, of course.