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Video TrainingRHEL 8 - Deploying, Configuring and Maintaining Systems





RHEL 8 - Deploying, Configuring and Maintaining Systems
Andrew Mallett | Duration: 2:13 h | Video: H264 1280x720 | Audio: AAC 48 kHz 2ch | 225 MB | Language: English + SUB
Everyday administration skills in Linux require you to be able to install software as a minimum. This course will teach you not only to install software but to be able to rollback software changes.
Ensuring that services are started automatically, especially the time service ensuring accurate time on your system, is essential. In this course, RHEL 8: Deploying, Configuring and Maintaining Systems, you'll learn to manage services, software and boot targets. First, you'll explore software management in RHEL 8. Next, you'll discover service management including configuring the chrony time client. Finally, you'll learn how to schedule tasks using the cron and at services. When you're finished with this course, you'll have the skills and knowledge of Linux administration needed to manage your enterprise servers.



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E-BooksDeploying OpenStack




Deploying OpenStack


Deploying OpenStack
pdf | 5.99 MB | English | Isbn:‎ 978-1491946695 | Author: Ken Pepple | Year: 2015





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Video TrainingApress - Building and Deploying Container Workloads on Azure From Docker Basics to Azure Container Instances



Apress - Building and Deploying Container Workloads on Azure From Docker Basics to Azure Container Instances

Apress - Building and Deploying Container Workloads on Azure From Docker Basics to Azure Container Instances-iLLiTERATE
English | Size: 319.92 MB
Category: Tutorial

This video is designed to take the viewer from zero to hero on building and deploying containerized workloads on Azure.

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Video TrainingBuilding and Deploying Container Workloads on Azure From Docker Basics to Azure Container Instances





Building and Deploying Container Workloads on Azure From Docker Basics to Azure Container Instances
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: Lessons (1h 13m) | Size: 186.2 MB
This video is designed to take the viewer from zero to hero on building and deploying containerized workloads on Azure.



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E-BooksPyTorch 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 (True PDF)
pdf | 6.75 MB | English | Isbn:‎ B094Q7YBTX | Author: Papa, Joe; | Year: 2021





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E-BooksPyTorch Pocket Reference Building and Deploying Deep Learning Models (True PDF)





PyTorch Pocket Reference Building and Deploying Deep Learning Models (True PDF)
English | 2021 | ISBN: 149209000X | 310 pages | True PDF | 6.75 MB
This concise, easy-to-use reference puts one of the most popular frameworks for deep learning research and development at your fingertips. Author Joe Papa provides instant access to syntax, design patterns, and code examples to accelerate your development and reduce the time you spend searching for answers.
Research scientists, machine learning engineers, and software developers will find clear, structured PyTorch code that covers every step of neural network developmentâ??from loading data to customizing training loops to model optimization and GPU/TPU acceleration. Quickly learn how to deploy your code to production using AWS, Google Cloud, or Azure and deploy your ML models to mobile and edge devices.



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E-BooksTensorFlow 2 Pocket Reference Building and Deploying Machine Learning Models





TensorFlow 2 Pocket Reference Building and Deploying Machine Learning Models
TensorFlow 2 Pocket Reference: Building and Deploying Machine Learning Models
English | 2021 | ISBN: 1492089184 | 300 Pages | EPUB | 11.44 MB
This easy-to-use reference for TensorFlow 2 design patterns in Python will help you make informed decisions for various use cases. Author KC Tung addresses common topics and tasks in enterprise data science and machine learning practices rather than focusing on TensorFlow itself. When and why would you feed training data as using NumPy or a streaming dataset? How would you set up cross-validations in the training process? How do you leverage a pretrained model using transfer learning? How do you perform hyperparameter tuning? Pick up this pocket reference and reduce the time you spend searching through options for your TensorFlow use cases. Understand best practices in TensorFlow model patterns and ML workflows Use code snippets as templates in building TensorFlow models and workflows Save development time by integrating prebuilt models in TensorFlow Hub Make informed design choices about data ingestion, training paradigms, model saving, and inferencing Address common scenarios such as model design style, data ingestion workflow, model training, and tuning



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Video TrainingPluralsight - Deploying Applications with TeamCity





Pluralsight - Deploying Applications with TeamCity
Duration: 1h 36m | Video: .MP4, 1280x720 30 fps | Audio: AAC, 48 kHz, 2ch | Size: 266 MB
Level: Intermediate | Genre: eLearning | Language: English
This course will teach you how to use TeamCity to deploy applications with an automated continuous delivery pipeline.



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Video TrainingPluralsight - Deploying Applications in Azure Kubernetes Service (AKS)





Pluralsight - Deploying Applications in Azure Kubernetes Service (AKS)
Duration: 33m | Video: .MP4, 1280x720 30 fps | Audio: AAC, 48 kHz, 2ch | Size: 91 MB
Level: Intermediate | Genre: eLearning | Language: English
Azure Kubernetes Service is a platform-as-a-service offering that provides you with a Kubernetes service in the Azure cloud. This course will teach you how to deploy applications in Azure Kubernetes Service.



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Video TrainingIIS Web Server Publishing and Deploying Web Applications





IIS Web Server Publishing and Deploying Web Applications
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 9 lectures (1h 8m) | Size: 575.3 MB
Mastering on deploying web apps in IIS Web Server: ASP.NET, ASP.NET Core, PHP, Node.js Express and Python Django



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