ISBN: 9798868819001 - practical rhel ai: designing, deploying and scaling ai solutions with red hat enterprise linux (21 resultados)

Condición: New.

Condición: New.

Paperback. Condición: New. First Edition. If you're looking to build, deploy, and scale AI solutions with confidence, Practical RHEL AI is the guide you need. Whether you're an AI developer, data scientist, or DevOps engineer, this book walks you through the entire process-from setting up your AI development environment to optimizing and securing enterprise-scale AI workloads on Red Hat Enterprise Linux.You'll start with the essentials: installation, configuration, and leveraging powerful machine learning frameworks like TensorFlow, PyTorch, and Scikit-learn. Then, you'll dive into the tools that make AI deployment seamless-GPU acceleration, containerization, and cloud integration with AWS and Azure.Security and compliance are non-negotiable in AI, and this book makes sure you get them right. Learn how to protect your models with encryption, implement role-based access control (RBAC), and meet industry standards like GDPR and HIPAA. You'll also master AI workload monitoring with Prometheus and Grafana, troubleshoot common issues, and automate deployments with Ansible. However, theory only gets you so far-real-world applications make the difference. Through hands-on examples and case studies in healthcare, finance, and manufacturing, you'll see how RHEL AI powers innovation in the field. Plus, you'll get insights into the future of AI, including Explainable AI (XAI), Edge AI, and AI governance. With Practical RHEL AI, you're not just learning AI-you're building AI solutions that scale.You Will:Learn to Install and Configure RHEL AI to optimize machine learning workloadsUnderstand how to train and Deploy AI models using TensorFlow, PyTorch, and Scikit-learnExplore how to Integrate and Implement GPU acceleration, cloud computing, and containerization for scalable AI solutionsLearn to Secure and Evaluate AI workloads with encryption, RBAC, and compliance best practices·      This Book is for:AI and machine learning engineers, DevOps and system administrators, Data scientists, and IT professionals and cloud architects.…

Condición: As New. Unread book in perfect condition.

Paperback. Condición: New. First Edition. If you're looking to build, deploy, and scale AI solutions with confidence, Practical RHEL AI is the guide you need. Whether you're an AI developer, data scientist, or DevOps engineer, this book walks you through the entire process-from setting up your AI development environment to optimizing and securing enterprise-scale AI workloads on Red Hat Enterprise Linux.You'll start with the essentials: installation, configuration, and leveraging powerful machine learning frameworks like TensorFlow, PyTorch, and Scikit-learn. Then, you'll dive into the tools that make AI deployment seamless-GPU acceleration, containerization, and cloud integration with AWS and Azure.Security and compliance are non-negotiable in AI, and this book makes sure you get them right. Learn how to protect your models with encryption, implement role-based access control (RBAC), and meet industry standards like GDPR and HIPAA. You'll also master AI workload monitoring with Prometheus and Grafana, troubleshoot common issues, and automate deployments with Ansible. However, theory only gets you so far-real-world applications make the difference. Through hands-on examples and case studies in healthcare, finance, and manufacturing, you'll see how RHEL AI powers innovation in the field. Plus, you'll get insights into the future of AI, including Explainable AI (XAI), Edge AI, and AI governance. With Practical RHEL AI, you're not just learning AI-you're building AI solutions that scale.You Will:Learn to Install and Configure RHEL AI to optimize machine learning workloadsUnderstand how to train and Deploy AI models using TensorFlow, PyTorch, and Scikit-learnExplore how to Integrate and Implement GPU acceleration, cloud computing, and containerization for scalable AI solutionsLearn to Secure and Evaluate AI workloads with encryption, RBAC, and compliance best practices·      This Book is for:AI and machine learning engineers, DevOps and system administrators, Data scientists, and IT professionals and cloud architects.…

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Condición: New.

Condición: As New. Unread book in perfect condition.

Taschenbuch. Condición: Sehr gut. Gebraucht - Sehr gut Leichte Lagerspuren -If you're looking to build, deploy, and scale AI solutions with confidence, Practical RHEL AI is the guide you need. Whether you're an AI developer, data scientist, or DevOps engineer, this book walks you through the entire process from setting up your AI development environment to optimizing and securing enterprise-scale AI workloads on Red Hat Enterprise Linux.You'll start with the essentials: installation, configuration, and leveraging powerful machine learning frameworks like TensorFlow, PyTorch, and Scikit-learn. Then, you ll dive into the tools that make AI deployment seamless GPU acceleration, containerization, and cloud integration with AWS and Azure.Security and compliance are non-negotiable in AI, and this book makes sure you get them right. Learn how to protect your models with encryption, implement role-based access control (RBAC), and meet industry standards like GDPR and HIPAA. You ll also master AI workload monitoring with Prometheus and Grafana, troubleshoot common issues, and automate deployments with Ansible.However,theory only gets you so far real-world applications make the difference. Through hands-on examples and case studies in healthcare, finance, and manufacturing, you ll see how RHEL AI powers innovation in the field. Plus, you'll get insights into the future of AI, including Explainable AI (XAI), Edge AI, and AI governance. With Practical RHEL AI, you re not just learning AI you re building AI solutions that scale.You Will:Learn to Install and Configure RHEL AI to optimize machine learning workloads 280 pp. Englisch.…

Taschenbuch. Condición: Neu. Neuware -Chapter 1: Introduction to RHEL AI.- Chapter 2: Setting Up RHEL AI.- Chapter 3: Exploring Core Components.- Chapter 4: Advanced Features of RHEL AI.- Chapter 5: Developing Custom AI Applications.- Chapter 6: Monitoring and Maintenance.- Chapter 7: Use Cases and Best Practices.- Chapter 8: Future Trends in RHEL AI.- Chapter 9: Community and Support.…

Paperback. Condición: New. First Edition. If you're looking to build, deploy, and scale AI solutions with confidence, Practical RHEL AI is the guide you need. Whether you're an AI developer, data scientist, or DevOps engineer, this book walks you through the entire process-from setting up your AI development environment to optimizing and securing enterprise-scale AI workloads on Red Hat Enterprise Linux.You'll start with the essentials: installation, configuration, and leveraging powerful machine learning frameworks like TensorFlow, PyTorch, and Scikit-learn. Then, you'll dive into the tools that make AI deployment seamless-GPU acceleration, containerization, and cloud integration with AWS and Azure.Security and compliance are non-negotiable in AI, and this book makes sure you get them right. Learn how to protect your models with encryption, implement role-based access control (RBAC), and meet industry standards like GDPR and HIPAA. You'll also master AI workload monitoring with Prometheus and Grafana, troubleshoot common issues, and automate deployments with Ansible. However, theory only gets you so far-real-world applications make the difference. Through hands-on examples and case studies in healthcare, finance, and manufacturing, you'll see how RHEL AI powers innovation in the field. Plus, you'll get insights into the future of AI, including Explainable AI (XAI), Edge AI, and AI governance. With Practical RHEL AI, you're not just learning AI-you're building AI solutions that scale.You Will:Learn to Install and Configure RHEL AI to optimize machine learning workloadsUnderstand how to train and Deploy AI models using TensorFlow, PyTorch, and Scikit-learnExplore how to Integrate and Implement GPU acceleration, cloud computing, and containerization for scalable AI solutionsLearn to Secure and Evaluate AI workloads with encryption, RBAC, and compliance best practices·      This Book is for:AI and machine learning engineers, DevOps and system administrators, Data scientists, and IT professionals and cloud architects.…

Taschenbuch. Condición: Neu. Neuware - If you're looking to build, deploy, and scale AI solutions with confidence, Practical RHEL AI is the guide you need. Whether you're an AI developer, data scientist, or DevOps engineer, this book walks you through the entire process from setting up your AI development environment to optimizing and securing enterprise-scale AI workloads on Red Hat Enterprise Linux.You'll start with the essentials: installation, configuration, and leveraging powerful machine learning frameworks like TensorFlow, PyTorch, and Scikit-learn. Then, you ll dive into the tools that make AI deployment seamless GPU acceleration, containerization, and cloud integration with AWS and Azure.Security and compliance are non-negotiable in AI, and this book makes sure you get them right. Learn how to protect your models with encryption, implement role-based access control (RBAC), and meet industry standards like GDPR and HIPAA. You ll also master AI workload monitoring with Prometheus and Grafana, troubleshoot common issues, and automate deployments with Ansible.However,theory only gets you so far real-world applications make the difference. Through hands-on examples and case studies in healthcare, finance, and manufacturing, you ll see how RHEL AI powers innovation in the field. Plus, you'll get insights into the future of AI, including Explainable AI (XAI), Edge AI, and AI governance. With Practical RHEL AI, you re not just learning AI you re building AI solutions that scale.You Will:Learn to Install and Configure RHEL AI to optimize machine learning workloads.…

Taschenbuch. Condición: Neu. Practical RHEL AI | Designing, Deploying and Scaling AI Solutions with Red Hat Enterprise Linux | Luca Berton | Taschenbuch | xix | Englisch | 2026 | Apress | EAN 9798868819001 | Verantwortliche Person für die EU: APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Paperback. Condición: New. First Edition. If you're looking to build, deploy, and scale AI solutions with confidence, Practical RHEL AI is the guide you need. Whether you're an AI developer, data scientist, or DevOps engineer, this book walks you through the entire process-from setting up your AI development environment to optimizing and securing enterprise-scale AI workloads on Red Hat Enterprise Linux.You'll start with the essentials: installation, configuration, and leveraging powerful machine learning frameworks like TensorFlow, PyTorch, and Scikit-learn. Then, you'll dive into the tools that make AI deployment seamless-GPU acceleration, containerization, and cloud integration with AWS and Azure.Security and compliance are non-negotiable in AI, and this book makes sure you get them right. Learn how to protect your models with encryption, implement role-based access control (RBAC), and meet industry standards like GDPR and HIPAA. You'll also master AI workload monitoring with Prometheus and Grafana, troubleshoot common issues, and automate deployments with Ansible. However, theory only gets you so far-real-world applications make the difference. Through hands-on examples and case studies in healthcare, finance, and manufacturing, you'll see how RHEL AI powers innovation in the field. Plus, you'll get insights into the future of AI, including Explainable AI (XAI), Edge AI, and AI governance. With Practical RHEL AI, you're not just learning AI-you're building AI solutions that scale.You Will:Learn to Install and Configure RHEL AI to optimize machine learning workloadsUnderstand how to train and Deploy AI models using TensorFlow, PyTorch, and Scikit-learnExplore how to Integrate and Implement GPU acceleration, cloud computing, and containerization for scalable AI solutionsLearn to Secure and Evaluate AI workloads with encryption, RBAC, and compliance best practices·      This Book is for:AI and machine learning engineers, DevOps and system administrators, Data scientists, and IT professionals and cloud architects.…

Taschenbuch. Condición: Neu. Neuware -If you're looking to build, deploy, and scale AI solutions with confidence, Practical RHEL AI is the guide you need. Whether you're an AI developer, data scientist, or DevOps engineer, this book walks you through the entire processfrom setting up your AI development environment to optimizing and securing enterprise-scale AI workloads on Red Hat Enterprise Linux.You'll start with the essentials: installation, configuration, and leveraging powerful machine learning frameworks like TensorFlow, PyTorch, and Scikit-learn. Then, you'll dive into the tools that make AI deployment seamlessGPU acceleration, containerization, and cloud integration with AWS and Azure.Security and compliance are non-negotiable in AI, and this book makes sure you get them right. Learn how to protect your models with encryption, implement role-based access control (RBAC), and meet industry standards like GDPR and HIPAA. You'll also master AI workload monitoring with Prometheus and Grafana, troubleshoot common issues, and automate deployments with Ansible. However, theory only gets you so farreal-world applications make the difference. Through hands-on examples and case studies in healthcare, finance, and manufacturing, you'll see how RHEL AI powers innovation in the field. Plus, you'll get insights into the future of AI, including Explainable AI (XAI), Edge AI, and AI governance. With Practical RHEL AI, you're not just learning AIyou're building AI solutions that scale.You Will:- Learn to Install and Configure RHEL AI to optimize machine learning workloads- Understand how to train and Deploy AI models using TensorFlow, PyTorch, and Scikit-learn- Explore how to Integrate and Implement GPU acceleration, cloud computing, and containerization for scalable AI solutions- Learn to Secure and Evaluate AI workloads with encryption, RBAC, and compliance best practices This Book is for:AI and machine learning engineers, DevOps and system administrators, Data scientists, and IT professionals and cloud architects 280 pp. Englisch.…

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -If you're looking to build, deploy, and scale AI solutions with confidence, Practical RHEL AI is the guide you need. Whether you're an AI developer, data scientist, or DevOps engineer, this book walks you through the entire process from setting up your AI development environment to optimizing and securing enterprise-scale AI workloads on Red Hat Enterprise Linux.You'll start with the essentials: installation, configuration, and leveraging powerful machine learning frameworks like TensorFlow, PyTorch, and Scikit-learn. Then, you ll dive into the tools that make AI deployment seamless GPU acceleration, containerization, and cloud integration with AWS and Azure.Security and compliance are non-negotiable in AI, and this book makes sure you get them right. Learn how to protect your models with encryption, implement role-based access control (RBAC), and meet industry standards like GDPR and HIPAA. You ll also master AI workload monitoring with Prometheus and Grafana, troubleshoot common issues, and automate deployments with Ansible.However,theory only gets you so far real-world applications make the difference. Through hands-on examples and case studies in healthcare, finance, and manufacturing, you ll see how RHEL AI powers innovation in the field. Plus, you'll get insights into the future of AI, including Explainable AI (XAI), Edge AI, and AI governance. With Practical RHEL AI, you re not just learning AI you re building AI solutions that scale.You Will:Learn to Install and Configure RHEL AI to optimize machine learning workloads 280 pp. Englisch.…

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -If you're looking to build, deploy, and scale AI solutions with confidence, Practical RHEL AI is the guide you need. Whether you're an AI developer, data scientist, or DevOps engineer, this book walks you through the entire process from setting up your AI development environment to optimizing and securing enterprise-scale AI workloads on Red Hat Enterprise Linux.You'll start with the essentials: installation, configuration, and leveraging powerful machine learning frameworks like TensorFlow, PyTorch, and Scikit-learn. Then, you ll dive into the tools that make AI deployment seamless GPU acceleration, containerization, and cloud integration with AWS and Azure.Security and compliance are non-negotiable in AI, and this book makes sure you get them right. Learn how to protect your models with encryption, implement role-based access control (RBAC), and meet industry standards like GDPR and HIPAA. You ll also master AI workload monitoring with Prometheus and Grafana, troubleshoot common issues, and automate deployments with Ansible.However,theory only gets you so far real-world applications make the difference. Through hands-on examples and case studies in healthcare, finance, and manufacturing, you ll see how RHEL AI powers innovation in the field. Plus, you'll get insights into the future of AI, including Explainable AI (XAI), Edge AI, and AI governance. With Practical RHEL AI, you re not just learning AI you re building AI solutions that scale.You Will:Learn to Install and Configure RHEL AI to optimize machine learning workloads 280 pp. Englisch.…

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.

Paperback. Condición: new. Paperback. If you're looking to build, deploy, and scale AI solutions with confidence, Practical RHEL AI is the guide you need. Whether you're an AI developer, data scientist, or DevOps engineer, this book walks you through the entire processfrom setting up your AI development environment to optimizing and securing enterprise-scale AI workloads on Red Hat Enterprise Linux.You'll start with the essentials: installation, configuration, and leveraging powerful machine learning frameworks like TensorFlow, PyTorch, and Scikit-learn. Then, youll dive into the tools that make AI deployment seamlessGPU acceleration, containerization, and cloud integration with AWS and Azure.Security and compliance are non-negotiable in AI, and this book makes sure you get them right. Learn how to protect your models with encryption, implement role-based access control (RBAC), and meet industry standards like GDPR and HIPAA. Youll also master AI workload monitoring with Prometheus and Grafana, troubleshoot common issues, and automate deployments with Ansible. However, theory only gets you so farreal-world applications make the difference. Through hands-on examples and case studies in healthcare, finance, and manufacturing, youll see how RHEL AI powers innovation in the field. Plus, you'll get insights into the future of AI, including Explainable AI (XAI), Edge AI, and AI governance. With Practical RHEL AI, youre not just learning AIyoure building AI solutions that scale.You Will:Learn to Install and Configure RHEL AI to optimize machine learning workloadsUnderstand how to train and Deploy AI models using TensorFlow, PyTorch, and Scikit-learnExplore how to Integrate and Implement GPU acceleration, cloud computing, and containerization for scalable AI solutionsLearn to Secure and Evaluate AI workloads with encryption, RBAC, and compliance best practices This Book is for:AI and machine learning engineers, DevOps and system administrators, Data scientists, and IT professionals and cloud architects This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -If you're looking to build, deploy, and scale AI solutions with confidence, Practical RHEL AI is the guide you need. Whether you're an AI developer, data scientist, or DevOps engineer, this book walks you through the entire processfrom setting up your AI development environment to optimizing and securing enterprise-scale AI workloads on Red Hat Enterprise Linux.Libri GmbH, Europaallee 1, 36244 Bad Hersfeld 280 pp. Englisch.…