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C# Cookbook
C# Cookbook

Even if you're familiar with C# syntax, knowing how to combine various language features is a critical skill when you're building applications. This cookbook is packed full of recipes to help you solve issues for C# programming tasks you're likely to encounter. You'll learn tried-and-true techniques to help you achieve greater productivity and improve the quality of your code. Author and independent consultant Joe Mayo shares some of the most important practices you'll need to be successful as a C# developer. Each section of this cookbook describes some useful facet of the C# programming language. These recipes - the result of many years of experience-are proven concepts for solving real-world problems with C#. Recipes in this book will help you: Set up your project, manage object lifetime, and establish patterns; Improve code quality through maintainability, error prevention, and correct syntax; Use LINQ to Objects for in-memory data manipulation and querying; Understand the dif ...
Cloud Design Patterns
Cloud Design Patterns

Cloud applications have a unique set of characteristics. They run on commodity hardware, provide services to untrusted users, and deal with unpredictable workloads. These factors impose a range of problems that you, as a designer or developer, need to resolve. Your applications must be resilient so that they can recover from failures, secure to protect services from malicious attacks, and elastic in order to respond to an ever changing workload. This guide demonstrates design patterns that can help you to solve the problems you might encounter in many different areas of cloud application development. Each pattern discusses design considerations, and explains how you can implement it using the features of Windows Azure. The patterns are grouped into categories: availability, data management, design and implementation, messaging, performance and scalability, resilience, management and monitoring, and security. You will also see more general guidance related to these areas of concern. It ...
MLOps Engineering at Scale
MLOps Engineering at Scale

MLOps Engineering at Scale shows you how to put machine learning into production efficiently by using pre-built services from AWS and other cloud vendors. You'll learn how to rapidly create flexible and scalable machine learning systems without laboring over time-consuming operational tasks or taking on the costly overhead of physical hardware. Following a real-world use case for calculating taxi fares, you will engineer an MLOps pipeline for a PyTorch model using AWS server-less capabilities. A production-ready machine learning system includes efficient data pipelines, integrated monitoring, and means to scale up and down based on demand. Using cloud-based services to implement ML infrastructure reduces development time and lowers hosting costs. Serverless MLOps eliminates the need to build and maintain custom infrastructure, so you can concentrate on your data, models, and algorithms. MLOps Engineering at Scale teaches you how to implement efficient machine learning systems usi ...
Kafka in Action
Kafka in Action

Kafka in Action is a fast-paced introduction to every aspect of working with Apache Kafka. Starting with an overview of Kafka's core concepts, you'll immediately learn how to set up and execute basic data movement tasks and how to produce and consume streams of events. Advancing quickly, you'll soon be ready to use Kafka in your day-to-day workflow, and start digging into even more advanced Kafka topics. Think of Apache Kafka as a high performance software bus that facilitates event streaming, logging, analytics, and other data pipeline tasks. With Kafka, you can easily build features like operational data monitoring and large-scale event processing into both large and small-scale applications. Kafka in Action introduces the core features of Kafka, along with relevant examples of how to use it in real applications. In it, you'll explore the most common use cases such as logging and managing streaming data. When you're done, you'll be ready to handle both basic developer- and admi ...
Fundamentals of Computer Programming with C#
Fundamentals of Computer Programming with C#

This open book aims to provide novice programmers solid foundation of basic knowledge regardless of the programming language. This book covers the fundamentals of programming that have not changed significantly over the last 10 years. Educational content was developed by an authoritative author team led by Svetlin Nakov from the Software University (SoftUni) and covers topics such as variables conditional statements, loops and arrays, and more complex concepts such as data structures (lists, stacks, queues, trees, hash tables, etc.), and recursion recursive algorithms, object-oriented programming and high-quality code. From the book you will learn how to think as programmers and how to solve efficiently programming problems. You will master the fundamental principles of programming and basic data structures and algorithms, without which you can't become a software engineer. If you want to learn programming and software development and become a software engineer and start a job in a ...
Microsoft Visual C# Step by Step, 10th Edition
Microsoft Visual C# Step by Step, 10th Edition

Expand your expertiseand teach yourself the fundamentals of programming the latest version of Visual C# with Visual Studio 2022. This book provides software developers all the guidance, exercises, and code needed to start building responsive, scalable, cloud-connected applications that can run almost anywhere. Discover how to: Quickly start creating Visual C# code and projects with Visual Studio; Work with variables, operators, expressions, methods, and program flow; Build more robust apps with error, exception, and resource management; Spot problems fast with the integrated Visual Studio 2022 debugger; Master new default interface methods, static local functions, async disposable types, and other enhancements; Make the most of the C# object model, and create functional data structures; Leverage advanced properties, indexers, generics, and collection classes; Create Windows 11 apps that share data, collaborate, and use cloud services; Use lightweight records to build immutable ref ...
Serverless Architectures on AWS, 2nd Edition
Serverless Architectures on AWS, 2nd Edition

Serverless Architectures on AWS, 2nd Edition teaches you how to design serverless systems. You'll discover the principles behind serverless architectures, and explore real-world case studies where companies used serverless architectures for their products. You won't just master the technical essentials - the book contains extensive coverage of balancing tradeoffs and making essential technical decisions. This new edition has been fully updated with new chapters covering current best practice, example architectures, and full coverage of the latest changes to AWS. Maintaining server hardware and software can cost a lot of time and money. Unlike traditional data center infrastructure, serverless architectures offload core tasks like data storage and hardware management to pre-built cloud services. Better yet, you can combine your own custom AWS Lambda functions with other serverless services to create features that automatically start and scale on demand, reduce hosting cost, and simpl ...
Computer Networks
Computer Networks

Computer Networks: A Systems Approach, Sixth Edition, explores the key principles of computer networking, using real world examples from network and protocol design. Using the Internet as the primary example, this best-selling classic textbook explains various protocols and networking technologies. The systems-oriented approach encourages students to think about how individual network components fit into a larger, complex system of interactions. This sixth edition contains completely updated content with expanded coverage of the topics of utmost importance to networking professionals and students, as provided by numerous contributors via a unique open source model developed jointly by the authors and publisher. Hallmark features of the book are retained, including chapter problem statements, which introduce issues to be examined; shaded sidebars that elaborate on a topic or introduce a related advanced topic; What's Next? discussions that deal with emerging issues in research, the c ...
Artificial Neural Networks with Java, 2nd Edition
Artificial Neural Networks with Java, 2nd Edition

Develop neural network applications using the Java environment. After learning the rules involved in neural network processing, this second edition shows you how to manually process your first neural network example. The book covers the internals of front and back propagation and helps you understand the main principles of neural network processing. You also will learn how to prepare the data to be used in neural network development and you will be able to suggest various techniques of data preparation for many unconventional tasks. This book discusses the practical aspects of using Java for neural network processing. You will know how to use the Encog Java framework for processing large-scale neural network applications. Also covered is the use of neural networks for approximation of non-continuous functions. In addition to using neural networks for regression, this second edition shows you how to use neural networks for computer vision. It focuses on image recognition such as the ...
Mastering Azure Machine Learning, 2nd Edition
Mastering Azure Machine Learning, 2nd Edition

Azure Machine Learning is a cloud service for accelerating and managing the machine learning (ML) project life cycle that ML professionals, data scientists, and engineers can use in their day-to-day workflows. This book covers the end-to-end ML process using Microsoft Azure Machine Learning, including data preparation, performing and logging ML training runs, designing training and deployment pipelines, and managing these pipelines via MLOps. The first section shows you how to set up an Azure Machine Learning workspace; ingest and version datasets; as well as preprocess, label, and enrich these datasets for training. In the next two sections, you'll discover how to enrich and train ML models for embedding, classification, and regression. You'll explore advanced NLP techniques, traditional ML models such as boosted trees, modern deep neural networks, recommendation systems, reinforcement learning, and complex distributed ML training techniques - all using Azure Machine Learning. T ...
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