Microsoft Cybersecurity Architect Exam Ref SC-100. Get certified with ease while learning how to develop highly effective cybersecurity strategies

Dwayne Natwick, Rod Trent

Microsoft Cybersecurity Architect Exam Ref SC-100 is a comprehensive guide that will help cybersecurity professionals design and evaluate the cybersecurity architecture of Microsoft cloud services. Complete with hands-on tutorials, projects, and self-assessment questions, you’ll have everything you need to pass the SC-100 exam.This book will take you through designing a strategy for a cybersecurity architecture and evaluating the governance, risk, and compliance (GRC) of the architecture. This will include cloud-only and hybrid infrastructures, where you’ll learn how to protect using the principles of zero trust, along with evaluating security operations and the overall security posture. To make sure that you are able to take the SC-100 exam with confidence, the last chapter of this book will let you test your knowledge with a mock exam and practice questions.By the end of this book, you’ll have the knowledge you need to plan, design, and evaluate cybersecurity for Microsoft cloud and hybrid infrastructures, and pass the SC-100 exam with flying colors.

Canvas Cookbook. Click here to enter text

Bhushan Purushottam Joshi, Eric Rowell

With the growing popularity of HTML5 Canvas, this book offers tailored recipes to help you develop portable applications, presentations, and games.The recipes are simple yet creative and build on each other. At every step, the book inspires the reader to develop his/her own recipe. From basic to advanced, every aspect of Canvas API has been covered to guide readers to develop their own application, presentation, or game.

Microsoft Dynamics GP 2010 Implementation. If you feel intimidated by the thought of implementing Microsoft Dynamics GP, this book will quickly overcome any doubts. It’s the simplest, clearest guide available to getting this sophisticated ERP application up and running successfully

Victoria Yudin

Microsoft Dynamics GP 2010 is a sophisticated Enterprise Resource Planning application with a multitude of features and options. The implementation of Dynamics GP is usually considered to be complex, and can be very confusing for users and consultants. This step-by-step guide will show you how to effectively implement Dynamics GP 2010 with ease.This focused, step-by-step tutorial covers the basics of Microsoft Dynamics GP, from licensing, to design, before moving on to more complex topics such as implementation and setup. You will learn how to install and configure Microsoft Dynamics GP 2010 from start to finish.This book will enable you to master the implementation of Microsoft Dynamics 2010 effectively. This book starts with how to plan and complete a successful Microsoft Dynamics GP 2010 implementation. You will then move on to learning who should be on the implementation team, what important questions should be asked and how to plan your infrastructure for Dynamics GP 2010. Detailed descriptions of all the setup options for the core Dynamics GP modules as well as practical advice on setup will help guide you through the myriad of options available in this powerful application. As you reach the end of the book you will learn how to import your initial data with illustrations and practical examples.

Creators of Intelligence. Industry secrets from AI leaders that you can easily apply to advance your data science career

Dr. Alex Antic, John K. Thompson

A Gartner prediction in 2018 led to numerous articles stating that 85% of AI and machine learning projects fail to deliver.” Although it's unclear whether a mass extinction event occurred for AI implementations at the end of 2022, the question remains: how can I ensure that my project delivers value and doesn't become a statistic?The demand for data scientists has only grown since 2015, when they were dubbed the new “rock stars” of business. But how can you become a data science rock star? As a new senior data leader, how can you build and manage a productive team? And what is the path to becoming a chief data officer?Creators of Intelligence is a collection of in-depth, one-on-one interviews where Dr. Alex Antic, a recognized data science leader, explores the answers to these questions and more with some of the world's leading data science leaders and CDOs.Interviews with: Cortnie Abercrombie, Edward Santow, Kshira Saagar, Charles Martin, Petar Veličković, Kathleen Maley, Kirk Borne, Nikolaj Van Omme, Jason Tamara Widjaja, Jon Whittle, Althea Davis, Igor Halperin, Christina Stathopoulos, Angshuman Ghosh, Maria Milosavljevic, Dr. Meri Rosich, Dat Tran, and Stephane Doyen.

Mastering Python Networking. Utilize Python packages and frameworks for network automation, monitoring, cloud, and management - Fourth Edition

Eric Chou

Networks in your infrastructure set the foundation for deploying, maintaining, and servicing applications. Python is the ideal language for network engineers to explore tools that were previously available to systems engineers and application developers. Mastering Python Networking, Fourth edition, guides you on a Python-driven journey from traditional network engineering to modern network development.This new edition incorporates the latest Python features and DevOps frameworks. In addition to new chapters on introducing Docker containers and Python 3 Async IO for network engineers, each chapter is updated with the latest libraries and working examples to ensure compatibility and clarity of the concepts.Starting with a basic overview of Python, the book teaches you how it can interact with both legacy and API-enabled network devices. You will learn to leverage high-level Python packages and frameworks to perform network automation tasks, monitoring, management, and enhanced network security, followed by AWS and Azure cloud networking. You will use Git for code management, GitLab for continuous integration, and Python-based testing tools to verify your network.By the end of this book, you'll be a confident network developer capable of automating modern infrastructure using Python, DevOps practices, and cloud technologies.

Business Intelligence with Databricks SQL. Concepts, tools, and techniques for scaling business intelligence on the data lakehouse

Vihag Gupta

In this new era of data platform system design, data lakes and data warehouses are giving way to the lakehouse – a new type of data platform system that aims to unify all data analytics into a single platform. Databricks, with its Databricks SQL product suite, is the hottest lakehouse platform out there, harnessing the power of Apache Spark™, Delta Lake, and other innovations to enable data warehousing capabilities on the lakehouse with data lake economics.This book is a comprehensive hands-on guide that helps you explore all the advanced features, use cases, and technology components of Databricks SQL. You’ll start with the lakehouse architecture fundamentals and understand how Databricks SQL fits into it. The book then shows you how to use the platform, from exploring data, executing queries, building reports, and using dashboards through to learning the administrative aspects of the lakehouse – data security, governance, and management of the computational power of the lakehouse. You’ll also delve into the core technology enablers of Databricks SQL – Delta Lake and Photon. Finally, you’ll get hands-on with advanced SQL commands for ingesting data and maintaining the lakehouse.By the end of this book, you’ll have mastered Databricks SQL and be able to deploy and deliver fast, scalable business intelligence on the lakehouse.

React and React Native. A complete hands-on guide to modern web and mobile development with React.js - Third Edition

Adam Boduch, Roy Derks

React and React Native, Facebook’s innovative User Interface (UI) libraries, are designed to help you build robust cross-platform web and mobile applications. This updated third edition is improved and updated to cover the latest version of React. The book particularly focuses on the latest developments in the React ecosystem, such as modern Hook implementations, code splitting using lazy components and Suspense, user interface framework components using Material-UI, and Apollo. In terms of React Native, the book has been updated to version 0.62 and demonstrates how to apply native UI components for your existing mobile apps using NativeBase.You will begin by learning about the essential building blocks of React components. Next, you’ll progress to working with higher-level functionalities in application development, before putting this knowledge to use by developing user interface components for the web and for native platforms. In the concluding chapters, you’ll learn how to bring your application together with a robust data architecture.By the end of this book, you’ll be able to build React applications for the web and React Native applications for multiple mobile platforms.

Practical Machine Learning with R. Define, build, and evaluate machine learning models for real-world applications

Brindha Priyadarshini Jeyaraman, Ludvig Renbo Olsen, Monicah Wambugu

With huge amounts of data being generated every moment, businesses need applications that apply complex mathematical calculations to data repeatedly and at speed. With machine learning techniques and R, you can easily develop these kinds of applications in an efficient way.Practical Machine Learning with R begins by helping you grasp the basics of machine learning methods, while also highlighting how and why they work. You will understand how to get these algorithms to work in practice, rather than focusing on mathematical derivations. As you progress from one chapter to another, you will gain hands-on experience of building a machine learning solution in R. Next, using R packages such as rpart, random forest, and multiple imputation by chained equations (MICE), you will learn to implement algorithms including neural net classifier, decision trees, and linear and non-linear regression. As you progress through the book, you’ll delve into various machine learning techniques for both supervised and unsupervised learning approaches. In addition to this, you’ll gain insights into partitioning the datasets and mechanisms to evaluate the results from each model and be able to compare them. By the end of this book, you will have gained expertise in solving your business problems, starting by forming a good problem statement, selecting the most appropriate model to solve your problem, and then ensuring that you do not overtrain it.