Learning NGUI for Unity. Leverage the power of NGUI for Unity to create stunning mobile and PC games and user interfaces

Charles Bernardoff, Charles Bernardoff (EURO)

Microsoft Application Virtualization Cookbook. Over 55 hands-on recipes covering the key aspects of a successful App-V deployment

James Henry F Preston, James Preston

Troubleshooting OpenStack. Click here to enter text

Tony Campbell

OpenStack is a collection of software projects that work together to provide a cloud fabric. OpenStack is one of the fastest growing open source projects in history that unlocks cloud computing for everyone. With OpenStack, you are able to create public or private clouds on your own hardware. The flexibility and control afforded by OpenStack puts the cloud within reach of anyone willing to learn this technology.Starting with an introduction to OpenStack troubleshooting tools, we’ll walk through each OpenStack service and how you can quickly diagnose, troubleshoot, and correct problems in your OpenStack. Understanding the various projects and how they interact is essential for anyone attempting to troubleshoot an OpenStack cloud. We will start by explaining each of the major components and the dependencies between them, and move on to show you how to identify and utilize an effective set of OpenStack troubleshooting tools and fix common Keystone problems. Next, we will expose you to common errors and problems you may encounter when using the OpenStack Block Storage service (Cinder). We will then examine Heat, the OpenStack Orchestration Service, where you will learn how to trace errors, determine their root cause, and effectively correct the issue.Finally, you will get to know the best practices to architect your OpenStack cloud in order to achieve optimal performance, availability, and reliability.

Functional Python Programming. Discover the power of functional programming, generator functions, lazy evaluation, the built-in itertools library, and monads - Second Edition

Steven F. Lott

If you’re a Python developer who wants to discover how to take the power of functional programming (FP) and bring it into your own programs, then this book is essential for you, even if you know next to nothing about the paradigm. Starting with a general overview of functional concepts, you’ll explore common functional features such as first-class and higher-order functions, pure functions, and more. You’ll see how these are accomplished in Python 3.6 to give you the core foundations you’ll build upon. After that, you’ll discover common functional optimizations for Python to help your apps reach even higher speeds. You’ll learn FP concepts such as lazy evaluation using Python’s generator functions and expressions. Moving forward, you’ll learn to design and implement decorators to create composite functions. You'll also explore data preparation techniques and data exploration in depth, and see how the Python standard library fits the functional programming model. Finally, to top off your journey into the world of functional Python, you’ll at look at the PyMonad project and some larger examples to put everything into perspective.

Multithreading with C# Cookbook. Quick answers to common problems - Second Edition

Evgenii Agafonov

Multi-core processors are synonymous with computing speed and power in today’s world, which is why multithreading has become a key concern for C# developers. Multithreaded code helps you create effective, scalable, and responsive applications.This is an easy-to-follow guide that will show you difficult programming problems in context. You will learn how to solve them with practical, hands-on, recipes. With these recipes, you’ll be able to start creating your own scalable and reliable multithreaded applications. Starting from learning what a thread is, we guide you through the basics and then move on to more advanced concepts such as task parallel libraries, C# asynchronous functions, and much more.Rewritten to the latest C# specification, C# 6, and updated with new and modern recipes to help you make the most of the hardware you have available, this book will help you push the boundaries of what you thought possible in C#.

LLM Design Patterns. A Practical Guide to Building Robust and Efficient AI Systems

Ken Huang

This practical guide for AI professionals enables you to build on the power of design patterns to develop robust, scalable, and efficient large language models (LLMs). Written by a global AI expert and popular author driving standards and innovation in Generative AI, security, and strategy, this book covers the end-to-end lifecycle of LLM development and introduces reusable architectural and engineering solutions to common challenges in data handling, model training, evaluation, and deployment.You’ll learn to clean, augment, and annotate large-scale datasets, architect modular training pipelines, and optimize models using hyperparameter tuning, pruning, and quantization. The chapters help you explore regularization, checkpointing, fine-tuning, and advanced prompting methods, such as reason-and-act, as well as implement reflection, multi-step reasoning, and tool use for intelligent task completion. The book also highlights Retrieval-Augmented Generation (RAG), graph-based retrieval, interpretability, fairness, and RLHF, culminating in the creation of agentic LLM systems.By the end of this book, you’ll be equipped with the knowledge and tools to build next-generation LLMs that are adaptable, efficient, safe, and aligned with human values.

Modernizing Legacy Applications to Microsoft Azure. Plan and execute your modernization journey seamlessly

Steve Read, Larry Mead, Bob Ellsworth

Organizations have varying circumstances, objectives, and prerequisites when contemplating a hyper-scale cloud solution transformation to a platform such as Azure. Modernizing Legacy Applications to Microsoft Azure uncovers potential scenarios and provides choices, methodologies, techniques, and prospective possibilities for transitioning from legacy applications to the Microsoft Azure environment.You’ll start by understanding the legacy systems and the main concerns regarding migration. Then, you’ll investigate why distributed architectures are compelling and the various components of the Azure platform needed during migration. After that, you’ll explore the approaches to modernizing legacy applications and the Rs of modernizing (i.e., rehost, refactor, rearchitect, and retire). You’ll also learn about integration approaches and potential pitfalls.By the end of this book, you’ll be well equipped to modernize your legacy workloads while being aware of pitfalls and best practices.

Python Machine Learning. Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2 - Third Edition

Sebastian Raschka, Vahid Mirjalili

Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. It acts as both a step-by-step tutorial, and a reference you'll keep coming back to as you build your machine learning systems.Packed with clear explanations, visualizations, and working examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, Raschka and Mirjalili teach the principles behind machine learning, allowing you to build models and applications for yourself.Updated for TensorFlow 2.0, this new third edition introduces readers to its new Keras API features, as well as the latest additions to scikit-learn. It's also expanded to cover cutting-edge reinforcement learning techniques based on deep learning, as well as an introduction to GANs. Finally, this book also explores a subfield of natural language processing (NLP) called sentiment analysis, helping you learn how to use machine learning algorithms to classify documents.This book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments.