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Podcasts
Joey D'Antoni, Louis Davidson, Allan Hirt, John Martin, ...
Deploying SQL Server on Azure virtual machines allows you to work on full versions of SQL Server in the cloud without having to maintain on-premises hardware. The book begins by introducing you to the SQL portfolio in Azure and takes you through SQL Server IaaS scenarios, before explaining the factors that you need to consider while choosing an OS for SQL Server in Azure VMs. As you progress through the book, you'll explore different VM options and deployment choices for IaaS and understand platform availability, migration tools, and best practices in Azure. In later chapters, you'll learn how to configure storage to achieve optimized performance. Finally, you'll get to grips with the concept of Azure Hybrid Benefit and find out how you can use it to maximize the value of your existing on-premises SQL Server.By the end of this book, you'll be proficient in administering SQL Server on Microsoft Azure and leveraging the tools required for its deployment.
One of the most valuable contributions of data science is toward helping businesses make the right decisions. Understanding this complicated confluence of two disparate worlds, as well as a fiercely competitive market, calls for all the guidance you can get.The Art of Data-Driven Business is your invaluable guide to gaining a business-driven perspective, as well as leveraging the power of machine learning (ML) to guide decision-making in your business. This book provides a common ground of discussion for several profiles within a company.You’ll begin by looking at how to use Python and its many libraries for machine learning. Experienced data scientists may want to skip this short introduction, but you’ll soon get to the meat of the book and explore the many and varied ways ML with Python can be applied to the domain of business decisions through real-world business problems that you can tackle by yourself. As you advance, you’ll gain practical insights into the value that ML can provide to your business, as well as the technical ability to apply a wide variety of tried-and-tested ML methods.By the end of this Python book, you’ll have learned the value of basing your business decisions on data-driven methodologies and have developed the Python skills needed to apply what you’ve learned in the real world.
Network analysis is often taught with tiny or toy data sets, leaving you with a limited scope of learning and practical usage. Network Science with Python helps you extract relevant data, draw conclusions and build networks using industry-standard – practical data sets. You’ll begin by learning the basics of natural language processing, network science, and social network analysis, then move on to programmatically building and analyzing networks. You’ll get a hands-on understanding of the data source, data extraction, interaction with it, and drawing insights from it. This is a hands-on book with theory grounding, specific technical, and mathematical details for future reference. As you progress, you’ll learn to construct and clean networks, conduct network analysis, egocentric network analysis, community detection, and use network data with machine learning. You’ll also explore network analysis concepts, from basics to an advanced level. By the end of the book, you’ll be able to identify network data and use it to extract unconventional insights to comprehend the complex world around you.
Mastering Salesforce Experience Cloud. Strategies for creating powerful customer interactions
Empowering your target audience to interact effortlessly with you and your product offerings is a critical aspect of business in the modern era. Users expect easy, professional digital experiences when engaging with organizations. However, creating engagement applications from scratch is challenging, and connecting user behavior with your organization’s data is even more complex. Enter Salesforce Experience Cloud sites, website portals built on the Salesforce data model that seamlessly connects your user data to your user experience. Mastering Salesforce Experience Cloud focuses on the human-centric nature of this product, beginning with a comprehensive guide on designing for your organization’s desired users and ensuring success for both internal teams and end users. After exploring the real-world applications of Experience Cloud and reviewing license models, this book provides a beginning-to-end guide to mastering the technical backend of this product, covering both out-of-the-box settings and customization techniques. By the end of this book, you’ll have gained a deep understanding of the Experience Cloud data model and customization options to create engaging, user-centric digital experiences that deliver value to your organization and stakeholders.
The kubectl command line tool lets you control Kubernetes clusters to manage nodes in the cluster and perform all types of Kubernetes operations. This introductory guide will get you up to speed with kubectl in no time.The book is divided into four parts, touching base on the installation and providing a general overview of kubectl in the first part. The second part introduces you to managing Kubernetes clusters and working with nodes. In the third part, you’ll be taken through the different ways in which you can manage Kubernetes applications, covering how to create, update, delete, view, and debug applications. The last part of the book focuses on various Kubernetes plugins and commands. You’ll get to grips with using Kustomize and discover Helm, a Kubernetes package manager. In addition to this, you’ll explore how you can use equivalent Docker commands in kubectl.By the end of this book, you’ll have learned how to install and update an application on Kubernetes, view its logs, and inspect clusters effectively.
Anubhav Singh, Rimjhim Bhadani
Deep learning is rapidly becoming the most popular topic in the mobile app industry. This book introduces trending deep learning concepts and their use cases with an industrial and application-focused approach. You will cover a range of projects covering tasks such as mobile vision, facial recognition, smart artificial intelligence assistant, augmented reality, and more.With the help of eight projects, you will learn how to integrate deep learning processes into mobile platforms, iOS, and Android. This will help you to transform deep learning features into robust mobile apps efficiently. You’ll get hands-on experience of selecting the right deep learning architectures and optimizing mobile deep learning models while following an application oriented-approach to deep learning on native mobile apps. We will later cover various pre-trained and custom-built deep learning model-based APIs such as machine learning (ML) Kit through Firebase. Further on, the book will take you through examples of creating custom deep learning models with TensorFlow Lite. Each project will demonstrate how to integrate deep learning libraries into your mobile apps, right from preparing the model through to deployment.By the end of this book, you’ll have mastered the skills to build and deploy deep learning mobile applications on both iOS and Android.