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Welcome to the Robot World … and start building intelligent software now!Through his best-selling video courses, Hadelin de Ponteves has taught hundreds of thousands of people to write AI software. Now, for the first time, his hands-on, energetic approach is available as a book. Starting with the basics before easing you into more complicated formulas and notation, AI Crash Course gives you everything you need to build AI systems with reinforcement learning and deep learning. Five full working projects put the ideas into action, showing step-by-step how to build intelligent software using the best and easiest tools for AI programming, including Python, TensorFlow, Keras, and PyTorch.AI Crash Course teaches everyone to build an AI to work in their applications. Once you've read this book, you're only limited by your imagination.
With the explosion of data, the open source Apache Hadoop ecosystem is gaining traction, thanks to its huge ecosystem that has arisen around the core functionalities of its distributed file system (HDFS) and Map Reduce. As of today, being able to have SQL Server talking to Hadoop has become increasingly important because the two are indeed complementary. While petabytes of unstructured data can be stored in Hadoop taking hours to be queried, terabytes of structured data can be stored in SQL Server 2012 and queried in seconds. This leads to the need to transfer and integrate data between Hadoop and SQL Server.Microsoft SQL Server 2012 with Hadoop is aimed at SQL Server developers. It will quickly show you how to get Hadoop activated on SQL Server 2012 (it ships with this version). Once this is done, the book will focus on how to manage big data with Hadoop and use Hadoop Hive to query the data. It will also cover topics such as using in-memory functions by SQL Server and using tools for BI with big data.Microsoft SQL Server 2012 with Hadoop focuses on data integration techniques between relational (SQL Server 2012) and non-relational (Hadoop) worlds. It will walk you through different tools for the bi-directional movement of data with practical examples.You will learn to use open source connectors like SQOOP to import and export data between SQL Server 2012 and Hadoop, and to work with leading in-memory BI tools to create ETL solutions using the Hive ODBC driver for developing your data movement projects. Finally, this book will give you a glimpse of the present day self-service BI tools such as Excel and PowerView to consume Hadoop data and provide powerful insights on the data.
Decentralizing data and centralizing governance are practical, scalable, and modern approaches to data analytics. However, implementing a data mesh can feel like changing the engine of a moving car. Most organizations struggle to start and get caught up in the concept of data domains, spending months trying to organize domains. This is where Engineering Data Mesh in Azure Cloud can help.The book starts by assessing your existing framework before helping you architect a practical design. As you progress, you’ll focus on the Microsoft Cloud Adoption Framework for Azure and the cloud-scale analytics framework, which will help you quickly set up a landing zone for your data mesh in the cloud.The book also resolves common challenges related to the adoption and implementation of a data mesh faced by real customers. It touches on the concepts of data contracts and helps you build practical data contracts that work for your organization. The last part of the book covers some common architecture patterns used for modern analytics frameworks such as artificial intelligence (AI).By the end of this book, you’ll be able to transform existing analytics frameworks into a streamlined data mesh using Microsoft Azure, thereby navigating challenges and implementing advanced architecture patterns for modern analytics workloads.
Explainable AI (XAI) is an emerging field that brings artificial intelligence (AI) closer to non-technical end users. XAI makes machine learning (ML) models transparent and trustworthy along with promoting AI adoption for industrial and research use cases.Applied Machine Learning Explainability Techniques comes with a unique blend of industrial and academic research perspectives to help you acquire practical XAI skills. You'll begin by gaining a conceptual understanding of XAI and why it's so important in AI. Next, you'll get the practical experience needed to utilize XAI in AI/ML problem-solving processes using state-of-the-art methods and frameworks. Finally, you'll get the essential guidelines needed to take your XAI journey to the next level and bridge the existing gaps between AI and end users.By the end of this ML book, you'll be equipped with best practices in the AI/ML life cycle and will be able to implement XAI methods and approaches using Python to solve industrial problems, successfully addressing key pain points encountered.
Toi B. Wright, Scott Hanselman
Blazor WebAssembly makes it possible to run C# code on the browser instead of having to use JavaScript, and does not rely on plugins or add-ons. The only technical requirement for using Blazor WebAssembly is a browser that supports WebAssembly, which, as of today, all modern browsers do. Blazor WebAssembly by Example is a project-based guide for learning how to build single-page web applications using the Blazor WebAssembly framework. This book emphasizes the practical over the theoretical by providing detailed step-by-step instructions for each project.You'll start by building simple standalone web applications and progress to developing more advanced hosted web applications with SQL Server backends. Each project covers a different aspect of the Blazor WebAssembly ecosystem, such as Razor components, JavaScript interop, event handling, application state, and dependency injection. The book is designed in such a way that you can complete the projects in any order.By the end of this book, you will have experience building a wide variety of single-page web applications with .NET, Blazor WebAssembly, and C#.
Generics were added as part of .NET Framework 2.0 in November 2005. Although similar to generics in Java, .NET generics do not apply type erasure but every object has unique representation at run-time. There is no performance hit from runtime casts and boxing conversions, which are normally expensive..NET offers type-safe versions of every classical data structure and some hybrid ones.This book will show you everything you need to start writing type-safe applications using generic data structures available in Generics API. You will also see how you can use several collections for each task you perform. This book is full of practical examples, interesting applications, and comparisons between Generics and more traditional approaches. Finally, each container is bench marked on the basis of performance for a given task, so you know which one to use and when.This book first covers the fundamental concepts such as type safety, Generic Methods, and Generic Containers. As the book progresses, you will learn how to join several generic containers to achieve your goals and query them efficiently using Linq. There are short exercises in every chapter to boost your knowledge.The book also teaches you some best practices, and several patterns that are commonly available in generic code.Some important generic algorithm definitions are present in Power Collection (an API created by Wintellect Inc.) that are missing from .NET framework. This book shows you how to use such algorithms seamlessly with other generic containers.The book also discusses C5 collections. Java Programmers will find themselves at home with this API. This is the closest to JCF. Some very interesting problems are solved using generic containers from .NET framework, C5, and PowerCollection Algorithms ñ a clone of Google Set and Gender Genie for example!The author has also created a website (https://www.consulttoday.com/genguide) for the book where you can find many useful tools, code snippets, and, applications, which are not the part of code-download section
David Álvarez Pérez, Ravikant Tiwari
Written by David Álvarez Pérez, a senior malware analyst at Gen Digital Inc., and Ravikant Tiwari, a senior security researcher at Microsoft, with expertise in malware and threat detection, this book is a complete guide to using Ghidra for examining malware, making patches, and customizing its features for your cybersecurity needs.This updated edition walks you through implementing Ghidra’s capabilities and automating reverse-engineering tasks with its plugins. You’ll learn how to set up an environment for practical malware analysis, use Ghidra in headless mode, and leverage Ghidra scripting to automate vulnerability detection in executable binaries. Advanced topics such as creating Ghidra plugins, adding new binary formats, analyzing processor modules, and contributing to the Ghidra project are thoroughly covered too.This edition also simplifies complex concepts such as remote and kernel debugging and binary diffing, and their practical uses, especially in malware analysis. From unpacking malware to analyzing modern ransomware, you’ll acquire the skills necessary for handling real-world cybersecurity challenges.By the end of this Ghidra book, you’ll be adept at avoiding potential vulnerabilities in code, extending Ghidra for advanced reverse-engineering, and applying your skills to strengthen your cybersecurity strategies.