Production-Ready Applied Deep Learning. Learn how to construct and deploy complex models in PyTorch and TensorFlow deep learning frameworks

Tomasz Palczewski, Jaejun (Brandon) Lee, Lenin Mookiah

Machine learning engineers, deep learning specialists, and data engineers encounter various problems when moving deep learning models to a production environment. The main objective of this book is to close the gap between theory and applications by providing a thorough explanation of how to transform various models for deployment and efficiently distribute them with a full understanding of the alternatives.First, you will learn how to construct complex deep learning models in PyTorch and TensorFlow. Next, you will acquire the knowledge you need to transform your models from one framework to the other and learn how to tailor them for specific requirements that deployment environments introduce. The book also provides concrete implementations and associated methodologies that will help you apply the knowledge you gain right away. You will get hands-on experience with commonly used deep learning frameworks and popular cloud services designed for data analytics at scale. Additionally, you will get to grips with the authors’ collective knowledge of deploying hundreds of AI-based services at a large scale.By the end of this book, you will have understood how to convert a model developed for proof of concept into a production-ready application optimized for a particular production setting.

Elasticsearch for Hadoop. Integrate Elasticsearch into Hadoop to effectively visualize and analyze your data

Vishal Shukla

The Machine Learning Solutions Architect Handbook. Create machine learning platforms to run solutions in an enterprise setting

David Ping

When equipped with a highly scalable machine learning (ML) platform, organizations can quickly scale the delivery of ML products for faster business value realization. There is a huge demand for skilled ML solutions architects in different industries, and this handbook will help you master the design patterns, architectural considerations, and the latest technology insights you’ll need to become one.You’ll start by understanding ML fundamentals and how ML can be applied to solve real-world business problems. Once you've explored a few leading problem-solving ML algorithms, this book will help you tackle data management and get the most out of ML libraries such as TensorFlow and PyTorch.Using open source technology such as Kubernetes/Kubeflow to build a data science environment and ML pipelines will be covered next, before moving on to building an enterprise ML architecture using Amazon Web Services (AWS). You’ll also learn about security and governance considerations, advanced ML engineering techniques, and how to apply bias detection, explainability, and privacy in ML model development. And finally, you'll get acquainted with AWS AI services and their applications in real-world use cases.By the end of this audiobook, you’ll be able to design and build an ML platform to support common use cases and architecture patterns like a true professional.

DevOps Adoption Strategies: Principles, Processes, Tools, and Trends. Embracing DevOps through effective culture, people, and processes

Martyn Coupland

DevOps is a set of best practices enabling operations and development teams to work together to produce higher-quality work and, among other things, quicker releases. This book helps you to understand the fundamentals needed to get started with DevOps, and prepares you to start deploying technical tools confidently.You will start by learning the key steps for implementing successful DevOps transformations. The book will help you to understand how aspects of culture, people, and process are all connected, and that without any one of these elements DevOps is unlikely to be successful. As you make progress, you will discover how to measure and quantify the success of DevOps in your organization, along with exploring the pros and cons of the main tooling involved in DevOps. In the concluding chapters, you will learn about the latest trends in DevOps and find out how the tooling changes when you work with these specialties.By the end of this DevOps book, you will have gained a clear understanding of the connection between culture, people, and processes within DevOps, and learned why all three are critically important.

Learning Veeam Backup & Replication for VMware vSphere. Learn how to protect your data in your VMware vSphere infrastructure with Veeam Backup & Replication

Christian Mohn

Learning DevOps. A comprehensive guide to accelerating DevOps culture adoption with Terraform, Azure DevOps, Kubernetes, and Jenkins - Second Edition

Mikael Krief

In the implementation of DevOps processes, the choice of tools is crucial to the sustainability of projects and collaboration between developers and ops. This book presents the different patterns and tools for provisioning and configuring an infrastructure in the cloud, covering mostly open source tools with a large community contribution, such as Terraform, Ansible, and Packer, which are assets for automation.This DevOps book will show you how to containerize your applications with Docker and Kubernetes and walk you through the construction of DevOps pipelines in Jenkins as well as Azure pipelines before covering the tools and importance of testing. You'll find a complete chapter on DevOps practices and tooling for open source projects before getting to grips with security integration in DevOps using Inspec, Hashicorp Vault, and Azure Secure DevOps kit. You'll also learn about the reduction of downtime with blue-green deployment and feature flags techniques before finally covering common DevOps best practices for all your projects.By the end of this book, you'll have built a solid foundation in DevOps and developed the skills necessary to enhance a traditional software delivery process using modern software delivery tools and techniques.

Azure Strategy and Implementation Guide. The essential handbook to cloud transformation with Azure - Fourth Edition

Jack Lee, Greg Leonardo, Jason Milgram, Dave Rendón

Microsoft Azure is a powerful cloud computing platform that offers a multitude of services and capabilities for organizations of any size moving to a cloud strategy.This fourth edition comes with the latest updates on cloud security fundamentals, hybrid cloud, cloud migration, Microsoft Azure Active Directory, and Windows Virtual Desktop. It encapsulates the entire spectrum of measures involved in Azure deployment that includes understanding Azure fundamentals, choosing a suitable cloud architecture, building on design principles, becoming familiar with Azure DevOps, and learning best practices for optimization and management.The book begins by introducing you to the Azure cloud platform and demonstrating the substantial scope of digital transformation and innovation that can be achieved with Azure's capabilities. The guide also acquaints you with practical insights into application modernization, Azure Infrastructure as a Service (IaaS) deployment, infrastructure management, key application architectures, best practices of Azure DevOps, and Azure automation.By the end of this book, you will have acquired the skills required to drive Azure operations from the planning and cloud migration stage to cost management and troubleshooting.

Jasmine JavaScript Testing. Test your JavaScript applications efficiently using Jasmine and React.js

Paulo Vitor Zacharias Ragonha