Tag: Deploying

  • Active Directory: Designing, Deploying, and Running Active Directory

    Active Directory: Designing, Deploying, and Running Active Directory


    Price: $52.53
    (as of Dec 17,2024 10:36:39 UTC – Details)




    Publisher ‏ : ‎ O’Reilly Media; 5th edition (June 25, 2013)
    Language ‏ : ‎ English
    Paperback ‏ : ‎ 735 pages
    ISBN-10 ‏ : ‎ 1449320023
    ISBN-13 ‏ : ‎ 978-1449320027
    Item Weight ‏ : ‎ 2.75 pounds
    Dimensions ‏ : ‎ 7 x 1.43 x 9.19 inches

    Customers say

    Customers find the book informative and easy to read. They say it provides a good overview of the inner workings of AD and is a good resource. Readers also mention that the content is thorough and easy to understand.

    AI-generated from the text of customer reviews


    Active Directory is a crucial component of many organizations’ IT infrastructure, serving as the centralized repository for user accounts, security policies, and network resources. Designing, deploying, and running Active Directory effectively is essential for ensuring a secure and efficient network environment.

    In this post, we will discuss key considerations and best practices for designing, deploying, and running Active Directory.

    Designing Active Directory:

    – Before deploying Active Directory, it is important to carefully plan the structure of the directory, including the organization of OUs (Organizational Units), groups, and domains. Consider factors such as the size and complexity of your organization, the number of users and resources, and any specific security requirements.
    – Designing a logical and efficient OU structure will make it easier to manage users, groups, and resources, and apply security policies and permissions.
    – Consider implementing a multi-domain or multi-forest design if your organization has multiple locations, business units, or security requirements that warrant separate domains or forests.

    Deploying Active Directory:

    – When deploying Active Directory, ensure that you have the necessary hardware and software requirements in place, including domain controllers, DNS servers, and network connectivity.
    – Follow best practices for installing and configuring domain controllers, including setting up replication, DNS integration, and FSMO roles.
    – Consider deploying additional domain controllers for redundancy and fault tolerance, especially in larger or geographically dispersed organizations.

    Running Active Directory:

    – Regularly monitor and maintain Active Directory to ensure optimal performance and security. This includes monitoring event logs, replication status, and the health of domain controllers.
    – Implement security best practices, such as using strong passwords, implementing group policies, and regularly auditing user accounts and permissions.
    – Back up Active Directory regularly to protect against data loss and ensure quick recovery in case of a disaster.

    By carefully designing, deploying, and running Active Directory, organizations can create a secure and efficient network environment that meets their business needs. Following best practices and staying proactive in monitoring and maintaining Active Directory will help organizations avoid downtime, security breaches, and data loss.
    #Active #Directory #Designing #Deploying #Running #Active #Directory

  • Programming PyTorch for Deep Learning: Creating and Deploying Deep Learni – GOOD

    Programming PyTorch for Deep Learning: Creating and Deploying Deep Learni – GOOD



    Programming PyTorch for Deep Learning: Creating and Deploying Deep Learni – GOOD

    Price : 19.60

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    Programming PyTorch for Deep Learning: Creating and Deploying Deep Learning Models

    Are you interested in diving into the world of deep learning using PyTorch? Look no further! In this post, we will explore how to create and deploy deep learning models using PyTorch, a popular open-source machine learning framework.

    PyTorch is known for its flexibility and ease of use, making it a great choice for both beginners and experienced developers. Whether you are looking to build a simple neural network or tackle more complex tasks like image recognition or natural language processing, PyTorch has you covered.

    In this post, we will cover the basics of setting up PyTorch, creating a simple neural network, training and evaluating the model, and finally deploying it for inference. We will also explore some best practices for optimizing and fine-tuning your models for better performance.

    So if you’re ready to take your deep learning skills to the next level, join us on this journey as we delve into the world of PyTorch and create powerful deep learning models. Stay tuned for more updates and tutorials on programming with PyTorch!
    #Programming #PyTorch #Deep #Learning #Creating #Deploying #Deep #Learni #GOOD

  • Pytorch Pocket Reference: Building And Deploying Deep Learning Models

    Pytorch Pocket Reference: Building And Deploying Deep Learning Models



    Pytorch Pocket Reference: Building And Deploying Deep Learning Models

    Price : 22.82

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    Pytorch Pocket Reference: Building And Deploying Deep Learning Models

    Are you looking to build and deploy deep learning models using Pytorch? Look no further! In this pocket reference guide, we will cover everything you need to know to get started with Pytorch.

    From setting up your environment to building and training your model, this reference guide will walk you through each step of the process. We will also cover how to deploy your model to production, so you can start using it in your applications right away.

    Whether you are a beginner or an experienced deep learning practitioner, this pocket reference guide is the perfect companion to help you build and deploy deep learning models with Pytorch. So grab your copy today and start creating amazing AI applications!
    #Pytorch #Pocket #Reference #Building #Deploying #Deep #Learning #Models

  • Programming PyTorch for Deep Learning: Creating and Deploying Deep Learning Appl

    Programming PyTorch for Deep Learning: Creating and Deploying Deep Learning Appl



    Programming PyTorch for Deep Learning: Creating and Deploying Deep Learning Appl

    Price : 20.37

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    Programming PyTorch for Deep Learning: Creating and Deploying Deep Learning Applications

    In this post, we will explore how to use PyTorch, a popular deep learning library, to create and deploy deep learning applications. PyTorch provides a flexible and powerful platform for building neural networks and training models for a variety of tasks, from image classification to natural language processing.

    We will start by discussing the basics of PyTorch, including tensors, neural networks, and optimization techniques. We will then delve into creating and training a deep learning model using PyTorch, exploring techniques such as data loading, model architecture design, loss function selection, and training loop implementation.

    Once we have trained our model, we will explore how to deploy it in a production environment. We will discuss techniques for optimizing and packaging models for deployment, as well as considerations for serving predictions at scale. We will also cover best practices for monitoring and maintaining deployed deep learning applications.

    Whether you are new to deep learning or looking to expand your skills with PyTorch, this post will provide you with the knowledge and tools you need to create and deploy powerful deep learning applications. Stay tuned for more updates on how to harness the full potential of PyTorch for your deep learning projects.
    #Programming #PyTorch #Deep #Learning #Creating #Deploying #Deep #Learning #Appl

  • Efficient AI Solutions: Deploying Deep Learning with ONNX and CUDA

    Efficient AI Solutions: Deploying Deep Learning with ONNX and CUDA


    Price: $29.99
    (as of Dec 17,2024 05:45:09 UTC – Details)



    In today’s rapidly evolving technological landscape, the demand for efficient AI solutions is higher than ever. One powerful tool that businesses are leveraging to meet this demand is deep learning, a subset of artificial intelligence that mimics the way the human brain works to process data and make decisions.

    To deploy deep learning models efficiently, many organizations are turning to the Open Neural Network Exchange (ONNX) format. ONNX is an open-source format that allows for interoperability between different deep learning frameworks, making it easier to transfer models between platforms and optimize performance.

    Another key component to efficient AI solutions is the use of CUDA, a parallel computing platform and application programming interface (API) model created by NVIDIA. CUDA allows developers to harness the power of NVIDIA graphics processing units (GPUs) to accelerate the training and inference of deep learning models, resulting in faster and more efficient processing.

    By combining the interoperability of ONNX with the parallel computing power of CUDA, businesses can deploy deep learning models quickly and efficiently, leading to improved performance and faster time to market. If you’re looking to harness the full potential of AI in your organization, consider incorporating ONNX and CUDA into your AI strategy for scalable and high-performing solutions.
    #Efficient #Solutions #Deploying #Deep #Learning #ONNX #CUDA

  • PyTorch Pocket Reference: Building and Deploying Deep Learning Models

    PyTorch Pocket Reference: Building and Deploying Deep Learning Models


    Price: $29.99 – $16.69
    (as of Dec 16,2024 15:53:03 UTC – Details)


    From the brand

    oreilly

    oreilly

    Explore our collection

    Oreilly

    Oreilly

    Sharing the knowledge of experts

    O’Reilly’s mission is to change the world by sharing the knowledge of innovators. For over 40 years, we’ve inspired companies and individuals to do new things (and do them better) by providing the skills and understanding that are necessary for success.

    Our customers are hungry to build the innovations that propel the world forward. And we help them do just that.

    Publisher ‏ : ‎ O’Reilly Media; 1st edition (June 15, 2021)
    Language ‏ : ‎ English
    Paperback ‏ : ‎ 307 pages
    ISBN-10 ‏ : ‎ 149209000X
    ISBN-13 ‏ : ‎ 978-1492090007
    Item Weight ‏ : ‎ 8 ounces
    Dimensions ‏ : ‎ 4.25 x 0.65 x 7 inches


    Are you looking to build and deploy deep learning models using PyTorch? Look no further! Our PyTorch Pocket Reference is the perfect guide for anyone wanting to master the art of building and deploying deep learning models.

    This comprehensive reference guide covers everything you need to know about PyTorch, from the basics of tensors and neural networks to advanced topics like transfer learning and model deployment. Whether you’re a beginner just getting started with deep learning or an experienced practitioner looking to expand your skills, this pocket reference has something for everyone.

    With easy-to-follow examples, code snippets, and practical tips, this reference guide will help you build and deploy deep learning models with ease. So, what are you waiting for? Grab your copy of the PyTorch Pocket Reference and start building cutting-edge deep learning models today!
    #PyTorch #Pocket #Reference #Building #Deploying #Deep #Learning #Models

  • Deep Learning with Pytorch: A Comprehensive Guide to Building, Training, and Deploying Advanced Neural Networks for Real-World Applications

    Deep Learning with Pytorch: A Comprehensive Guide to Building, Training, and Deploying Advanced Neural Networks for Real-World Applications


    Price: $29.99
    (as of Dec 16,2024 04:46:50 UTC – Details)




    ASIN ‏ : ‎ B0DJ6YTN63
    Publication date ‏ : ‎ September 28, 2024
    Language ‏ : ‎ English
    File size ‏ : ‎ 2516 KB
    Simultaneous device usage ‏ : ‎ Unlimited
    Text-to-Speech ‏ : ‎ Enabled
    Screen Reader ‏ : ‎ Supported
    Enhanced typesetting ‏ : ‎ Enabled
    X-Ray ‏ : ‎ Not Enabled
    Word Wise ‏ : ‎ Not Enabled
    Print length ‏ : ‎ 96 pages


    Deep Learning with Pytorch: A Comprehensive Guide to Building, Training, and Deploying Advanced Neural Networks for Real-World Applications

    In recent years, deep learning has emerged as a powerful tool for solving complex problems in various fields such as computer vision, natural language processing, and speech recognition. Pytorch, an open-source machine learning library developed by Facebook, has become one of the most popular frameworks for building and training deep neural networks.

    This comprehensive guide will take you through the fundamentals of deep learning with Pytorch, from building your first neural network to deploying advanced models for real-world applications. We will cover topics such as:

    – Understanding the basics of neural networks and deep learning
    – Building and training convolutional neural networks (CNNs) for image recognition
    – Implementing recurrent neural networks (RNNs) for sequence prediction tasks
    – Fine-tuning pre-trained models for transfer learning
    – Deploying models using Pytorch’s deployment options such as TorchServe

    Whether you are a beginner looking to get started with deep learning or an experienced practitioner looking to enhance your skills, this guide will provide you with the knowledge and tools you need to build, train, and deploy advanced neural networks for real-world applications using Pytorch. Stay tuned for more updates and in-depth tutorials on deep learning with Pytorch!
    #Deep #Learning #Pytorch #Comprehensive #Guide #Building #Training #Deploying #Advanced #Neural #Networks #RealWorld #Applications

  • Mastering AWS for Cloud Professionals: Architecting, deploying, and managing cloud solutions on AWS (English Edition)

    Mastering AWS for Cloud Professionals: Architecting, deploying, and managing cloud solutions on AWS (English Edition)


    Price: $39.95
    (as of Dec 16,2024 00:04:03 UTC – Details)



    In today’s digital world, cloud computing has become an essential part of businesses looking to scale and innovate rapidly. With Amazon Web Services (AWS) leading the way in cloud services, mastering AWS is crucial for cloud professionals looking to architect, deploy, and manage cloud solutions effectively.

    In our latest eBook, “Mastering AWS for Cloud Professionals”, we provide comprehensive guidance on how to navigate the AWS platform and leverage its services to build robust and scalable cloud solutions. From understanding the fundamentals of AWS to advanced topics like serverless computing and machine learning, this book covers everything you need to know to excel in the world of cloud computing.

    Whether you’re a seasoned cloud professional looking to upskill or a newcomer to the field, “Mastering AWS for Cloud Professionals” offers practical insights, real-world examples, and hands-on exercises to help you become an AWS expert. Get your copy today and take your cloud computing skills to the next level!
    #Mastering #AWS #Cloud #Professionals #Architecting #deploying #managing #cloud #solutions #AWS #English #Edition

  • Programming PyTorch for Deep Learning: Creating and Deploying Deep Learning Applications

    Programming PyTorch for Deep Learning: Creating and Deploying Deep Learning Applications


    Price: $55.99 – $33.49
    (as of Dec 15,2024 22:23:19 UTC – Details)


    From the brand

    oreilly

    oreilly

    Explore our collection

    Oreilly

    Oreilly

    Sharing the knowledge of experts

    O’Reilly’s mission is to change the world by sharing the knowledge of innovators. For over 40 years, we’ve inspired companies and individuals to do new things (and do them better) by providing the skills and understanding that are necessary for success.

    Our customers are hungry to build the innovations that propel the world forward. And we help them do just that.

    Publisher ‏ : ‎ O’Reilly Media; 1st edition (October 29, 2019)
    Language ‏ : ‎ English
    Paperback ‏ : ‎ 217 pages
    ISBN-10 ‏ : ‎ 1492045357
    ISBN-13 ‏ : ‎ 978-1492045359
    Item Weight ‏ : ‎ 2.31 pounds
    Dimensions ‏ : ‎ 7 x 0.5 x 9 inches


    Programming PyTorch for Deep Learning: Creating and Deploying Deep Learning Applications

    PyTorch has become one of the most popular frameworks for deep learning due to its flexibility, ease of use, and powerful capabilities. In this post, we will explore how to program with PyTorch to create and deploy deep learning applications.

    First, we will cover the basics of PyTorch, including tensors, neural networks, and optimization techniques. We will then dive into creating a deep learning model using PyTorch and training it on a dataset. We will discuss best practices for designing and training deep learning models, as well as how to evaluate their performance.

    Next, we will explore how to deploy deep learning applications using PyTorch. We will discuss techniques for optimizing models for deployment, including quantization and model compression. We will also cover how to deploy PyTorch models on different platforms, such as mobile devices or the cloud.

    Overall, this post will provide you with a comprehensive overview of programming with PyTorch for deep learning, from creating models to deploying them in production. Whether you are a beginner or an experienced deep learning practitioner, this post will help you take your skills to the next level.
    #Programming #PyTorch #Deep #Learning #Creating #Deploying #Deep #Learning #Applications

  • Cloud Native DevOps with Kubernetes: Building, Deploying, and Scaling Modern…

    Cloud Native DevOps with Kubernetes: Building, Deploying, and Scaling Modern…



    Cloud Native DevOps with Kubernetes: Building, Deploying, and Scaling Modern…

    Price : 8.27

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    Applications

    In today’s fast-paced digital world, cloud native development and DevOps practices have become essential for building, deploying, and scaling modern applications. Kubernetes, an open-source container orchestration platform, has emerged as a key tool in enabling organizations to achieve these goals.

    In this post, we will explore how Kubernetes is revolutionizing the way applications are built and deployed in the cloud native environment. We will delve into the key principles of cloud native DevOps with Kubernetes and discuss how organizations can leverage this powerful technology to streamline their development and deployment processes.

    From automating application deployment to scaling applications dynamically, Kubernetes provides a robust platform for managing containerized applications in a cloud native environment. By adopting Kubernetes, organizations can benefit from increased agility, scalability, and efficiency in their software development practices.

    Join us as we dive into the world of cloud native DevOps with Kubernetes and discover how you can build, deploy, and scale modern applications with ease and confidence. Stay tuned for expert insights, best practices, and practical tips on harnessing the power of Kubernetes for your development projects.
    #Cloud #Native #DevOps #Kubernetes #Building #Deploying #Scaling #Modern..

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