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Beginning with basic concepts like central tendency, dispersion, and types of distribution, this course will help you build a robust understanding of data analysis. It progresses to more advanced topics, including hypothesis testing, outliers, and the intricacies of dependent versus independent variables, ensuring you grasp the statistical tools necessary for data-driven decision-making.Moving ahead, you'll explore the mathematical frameworks crucial for machine learning algorithms. Learn about the significance of percentiles, the distinction between population and sample, and the vital role of precision versus accuracy in data science. Chapters on linear algebra and regression will enhance your ability to implement and interpret complex models, while practical lessons on measuring algorithm accuracy and understanding key machine learning concepts will round out your expertise.The course culminates with an in-depth look at specific machine learning techniques such as decision trees, k-nearest neighbors (kNN), and gradient descent. Each chapter builds on the last, guiding you through a logical progression of knowledge and skills. By the end, you will have not only mastered the theoretical aspects but also gained practical insights into applying these techniques in real-world scenarios.
Microsoft Dynamics 365 provides a vast array of tools and applications to meet various Customer Engagement requirements. This Customer Relationship Management (CRM) guide covers the latest advancements in Dynamics 365 and Power Platform that help organizations adapt to changing market conditions for agility and resilience.With this book, you'll explore the core platform functionality of Dynamics 365 and explore its wide range of components for transforming your business with new services and capabilities. You’ll learn the basics of configuration and customization to enhance the functionality of Microsoft Dynamics 365 CRM and create solutions and custom applications by leveraging features such as apps, portals, automation, and business intelligence. As you advance, you’ll understand how Power Platform drives Dynamics 365 and how various integration capabilities add value by providing a comprehensive view of data aggregated across different systems and data sources. Finally, you’ll delve into core administration concepts that will help you to manage extensions added to the platform.By the end of this book, you’ll have learned how to tailor Microsoft Dynamics 365 to fit your organization’s requirements and tweak the platform to meet your business needs.
The CISSP exam is for security professionals who understand that poor security can put a company out of business. The exam covers eight important security domains - risk management, security architecture, data security, network security, identity management, auditing, security operations, and software development security. Designed to cover all the concepts tested in the CISSP exam, CISSP (ISC)2 Certification Practice Exams and Tests will assess your knowledge of information security and introduce you to the tools you need to master to pass the CISSP exam (version May 2021). With more than 100 questions for every CISSP domain, this book will test your understanding and fill the gaps in your knowledge with the help of descriptive answers and detailed explanations. You'll also find two complete practice exams that simulate the real CISSP exam, along with answers. By the end of this book, you'll be ready to take and pass the (ISC)2 CISSP exam and achieve the Certified Information Systems Security Professional certification putting you in the position to build a career as a security engineer, security manager, or chief information security officer (CISO)
The Windows Server Automation with PowerShell Cookbook is back with a new edition, featuring over 100 PowerShell recipes that will make your day-to-day work easier. This book is designed to help you learn how to install, configure and use PowerShell 7.2 effectively.To start with, we’ll look at how to install and configure PowerShell 7.2, along with useful new features and optimizations, and show you how the PowerShell compatibility solution bridges the gap to older versions of PowerShell. We’ll also be covering a wide range of fundamental and more advanced use cases, including how to create a VM and set up an Azure VPN, as well as looking at how to back up to Azure. As you progress, you’ll explore topics such as using PowerShell to manage networking and DHCP in Windows Server, objects in Active Directory, Hyper-V, and Azure. We’ll also take a closer look at WSUS, containers and see how to handle modules that are not directly compatible with PowerShell 7. Finally, you’ll also learn how to use some powerful tools to diagnose and resolve issues with Windows Server.By the end of this PowerShell book, you’ll know how to use PowerShell 7.2 to automate tasks on Windows Server 2022 with ease, helping your Windows environment to run faster and smoother.
Luis Pedro Coelho, Willi Richert, Matthieu Brucher
Machine learning enables systems to make predictions based on historical data. Python is one of the most popular languages used to develop machine learning applications, thanks to its extensive library support. This updated third edition of Building Machine Learning Systems with Python helps you get up to speed with the latest trends in artificial intelligence (AI).With this guide’s hands-on approach, you’ll learn to build state-of-the-art machine learning models from scratch. Complete with ready-to-implement code and real-world examples, the book starts by introducing the Python ecosystem for machine learning. You’ll then learn best practices for preparing data for analysis and later gain insights into implementing supervised and unsupervised machine learning techniques such as classification, regression and clustering. As you progress, you’ll understand how to use Python’s scikit-learn and TensorFlow libraries to build production-ready and end-to-end machine learning system models, and then fine-tune them for high performance.By the end of this book, you’ll have the skills you need to confidently train and deploy enterprise-grade machine learning models in Python.