Wydawca: Packt Publishing
Refactoring in Java. Improving code design and maintainability for Java developers
Stefano Violetta
Refactoring in Java serves as an indispensable guide to enhancing your codebase’s quality and maintainability.The book begins by helping you get to grips with refactoring fundamentals, including cultivating good coding habits and identifying red flags. You’ll explore testing methodologies, essential refactoring techniques, and metaprogramming, as well as designing a good architecture. The chapters clearly explain how to refactor and improve your code using real-world examples and proven techniques. Part two equips you with the ability to recognize code smells, prioritize tasks, and employ automated refactoring tools, testing frameworks, and code analysis tools. You’ll discover best practices to ensure efficient code improvement so that you can navigate complexities with ease. In part three, the book focuses on continuous learning, daily practices enhancing coding proficiency, and a holistic view of the architecture. You’ll get practical tips to mitigate risks during refactoring, along with guidance on measuring impact to ensure that you become an efficient software craftsperson.By the end of this book, you’ll be able to avoid unproductive programming or architecturing, detect red flags, and propose changes to improve the maintainability of your codebase.
Refactoring TypeScript. Keeping your code healthy
James Hickey
Refactoring improves your code without changing its behavior. With refactoring, the best approach is to apply small targeted changes to a codebase. Instead of doing a huge sweeping change to your code, refactoring is better as a long-term and continuous enterprise. Refactoring TypeScript explains how to spot bugs and remove them from your code.You’ll start by seeing how wordy conditionals, methods, and null checks make code unhealthy and unstable. Whether it is identifying messy nested conditionals or removing unnecessary methods, this book will show various techniques to avoid these pitfalls and write code that is easier to understand, maintain, and test.By the end of the book, you’ll have learned some of the main causes of unhealthy code, tips to identify them and techniques to address them.
Refactoring with C++. Explore modern ways of developing maintainable and efficient applications
Dmitry Danilov
Despite the prevalence of higher-level languages, C++ is still running the world, from bare-metal embedded systems to distributed cloud-native systems. C++ is on the frontline whenever there is a need for a performance-sensitive tool supporting complex data structures. The language has been actively evolving for the last two decades.This book is a comprehensive guide that shows you how to implement SOLID principles and refactor legacy code using the modern features and approaches of C++, the standard library, Boost library collection, and Guidelines Support Library by Microsoft. The book begins by describing the essential elements of writing clean code and discussing object-oriented programming in C++. You’ll explore the design principles of software testing with examples of using popular unit testing frameworks such as Google Test. The book also guides you through applying automated tools for static and dynamic code analysis using Clang Tools.By the end of this book, you’ll be proficient in applying industry-approved coding practices to design clean, sustainable, and readable real-world C++ code.
Matt Eland, Steve Smith
Software projects start as brand-new greenfield projects, but invariably become muddied in technical debt far sooner than you’d expect. In Refactoring with C#, you'll explore what technical debt is and how it arises before walking through the process of safely refactoring C# code using modern tooling in Visual Studio and more recent C# language features using C# 12 and .NET 8. This book, written by a Microsoft MVP, will guide you through the process of refactoring safely through advanced unit testing with XUnit and libraries like Moq, Snapper, and Scientist .NET. You'll explore maintainable code through SOLID principles and defensive coding techniques made possible in newer versions of C#. You'll also find out how to run code analysis and write custom Roslyn analyzers to detect and resolve issues unique to your code.The nature of coding is changing, and you'll explore how to use AI with the GitHub Copilot Chat to refactor, test, document, and generate code before ending with a discussion about communicating technical debt to leadership and getting organizational buy-in to refactor your code in enterprise organizations and in agile teams.By the end of this book, you'll understand the nature of refactoring and see how you can safely, effectively, and repeatably pay down the technical debt in your application while adding value to your business.
Luca Massaron, Alberto Boschetti
Regression is the process of learning relationships between inputs and continuous outputs from example data, which enables predictions for novel inputs. There are many kinds of regression algorithms, and the aim of this book is to explain which is the right one to use for each set of problems and how to prepare real-world data for it. With this book you will learn to define a simple regression problem and evaluate its performance. The book will help you understand how to properly parse a dataset, clean it, and create an output matrix optimally built for regression. You will begin with a simple regression algorithm to solve some data science problems and then progress to more complex algorithms. The book will enable you to use regression models to predict outcomes and take critical business decisions. Through the book, you will gain knowledge to use Python for building fast better linear models and to apply the results in Python or in any computer language you prefer.
Giuseppe Ciaburro
Regression analysis is a statistical process which enables prediction of relationships between variables. The predictions are based on the casual effect of one variable upon another. Regression techniques for modeling and analyzing are employed on large set of data in order to reveal hidden relationship among the variables.This book will give you a rundown explaining what regression analysis is, explaining you the process from scratch. The first few chapters give an understanding of what the different types of learning are – supervised and unsupervised, how these learnings differ from each other. We then move to covering the supervised learning in details covering the various aspects of regression analysis. The outline of chapters are arranged in a way that gives a feel of all the steps covered in a data science process – loading the training dataset, handling missing values, EDA on the dataset, transformations and feature engineering, model building, assessing the model fitting and performance, and finally making predictions on unseen datasets. Each chapter starts with explaining the theoretical concepts and once the reader gets comfortable with the theory, we move to the practical examples to support the understanding. The practical examples are illustrated using R code including the different packages in R such as R Stats, Caret and so on. Each chapter is a mix of theory and practical examples.By the end of this book you will know all the concepts and pain-points related to regression analysis, and you will be able to implement your learning in your projects.
Sathish Veerapandian, Harsharanjeet Kaur, Ashok Madhvarayan, Sriram...
The outbreak of the pandemic has forced the world to embrace remote working and the modern style of virtual business. However, end users may find it challenging to cope with this sudden change in working style, not aware of all the features and remote working tools available to make their life easy. Microsoft Teams is an exceptional platform, adopted by many organizations for unified communication and collaboration, and this book will help you to make the most of its capabilities.Complete with step-by-step explanations and screenshots, this book guides you through the topics that you'll find useful in your daily use of Teams. You'll learn how to manage your teams and projects with Microsoft Teams in a structured and organized way. The book provides hands-on information with a focus on the end user side to help corporate users to increase productivity and become a Microsoft Teams superuser. Finally, you'll explore the most effective ways of using the app with best practices and tips and tricks for making the most of the features available for your scenario.By the end of this Microsoft Teams book, you'll have mastered Microsoft Teams and be fully equipped as a modern collaboration end user to effectively increase your remote work productivity.
Brian Rossney, Ciaran Kavanagh
MetaHuman Creator (MHC) is an online, user-friendly 3D design tool for creating highly realistic digital humans that can be animated within Unreal Engine (UE) and enhanced with motion capture technology. This means that filmmakers and game developers now have access to a high quality, affordable solution that was previously only available to specialist studios.This book will focus on using UE5 and MHC from a filmmaker angle. Firstly, you’ll understand how to use the online MHC to create a digital character, changing its facial structure, body type, and clothing. After that, you’ll learn all the necessary steps to bring the character into UE5 and set it up for animation. Then, using an iPhone and a webcam to capture face and body movements, you’ll mix these motion capture files, refine the animations using the MetaHuman Control Rig, and save these takes to be reused and edited again within the Level Sequencer. On top of that, you’ll learn how to create a rendered video file for film production using both the Level Sequencer and a VR Cinematic Camera. By the end of this book, you’ll have created your own MetaHuman character, as well as face and body motion capture data, and learned the necessary skills to give your future projects further realism and creative control.
Andrea Lonza
Reinforcement Learning (RL) is a popular and promising branch of AI that involves making smarter models and agents that can automatically determine ideal behavior based on changing requirements. This book will help you master RL algorithms and understand their implementation as you build self-learning agents.Starting with an introduction to the tools, libraries, and setup needed to work in the RL environment, this book covers the building blocks of RL and delves into value-based methods, such as the application of Q-learning and SARSA algorithms. You'll learn how to use a combination of Q-learning and neural networks to solve complex problems. Furthermore, you'll study the policy gradient methods, TRPO, and PPO, to improve performance and stability, before moving on to the DDPG and TD3 deterministic algorithms. This book also covers how imitation learning techniques work and how Dagger can teach an agent to drive. You'll discover evolutionary strategies and black-box optimization techniques, and see how they can improve RL algorithms. Finally, you'll get to grips with exploration approaches, such as UCB and UCB1, and develop a meta-algorithm called ESBAS.By the end of the book, you'll have worked with key RL algorithms to overcome challenges in real-world applications, and be part of the RL research community.
Sayon Dutta
Reinforcement learning (RL) allows you to develop smart, quick and self-learning systems in your business surroundings. It's an effective method for training learning agents and solving a variety of problems in Artificial Intelligence - from games, self-driving cars and robots, to enterprise applications such as data center energy saving (cooling data centers) and smart warehousing solutions.The book covers major advancements and successes achieved in deep reinforcement learning by synergizing deep neural network architectures with reinforcement learning. You'll also be introduced to the concept of reinforcement learning, its advantages and the reasons why it's gaining so much popularity. You'll explore MDPs, Monte Carlo tree searches, dynamic programming such as policy and value iteration, and temporal difference learning such as Q-learning and SARSA. You will use TensorFlow and OpenAI Gym to build simple neural network models that learn from their own actions. You will also see how reinforcement learning algorithms play a role in games, image processing and NLP.By the end of this book, you will have gained a firm understanding of what reinforcement learning is and understand how to put your knowledge to practical use by leveraging the power of TensorFlow and OpenAI Gym.
Remote Usability Testing. Actionable insights in user behavior across geographies and time zones
Inge De Bleecker, Rebecca Okoroji
Usability testing is a subdiscipline of User Experience. Its goal is to ensure that a given product is easy to use and the user's experience with the product is intuitive and satisfying. Usability studies are conducted with study participants who are representative of the target users to gather feedback on a user interface. The feedback is then used to refine and improve the user interface.Remote studies involve fewer logistics, allow participation regardless of location and are quicker and cheaper to execute compared to in person studies, while delivering valuable insights. The users are not inhibited by being in a new environment under observation; they can act naturally in their familiar environment. Remote unmoderated studies additionally have the advantage of being independent of time zones.This book will teach you how to conduct qualitative remote usability studies, in particular remote moderated and unmoderated studies. Each chapter provides actionable tips on how to use each methodology and how to compensate for the specific nature of each methodology. The book also provides material to help with planning and executing each study type.
Bryan Feuling
The world of software delivery and deployment has come a long way in the last few decades. From waterfall methods to Agile practices, every company that develops its own software has to overcome various challenges in delivery and deployment to meet customer and market demands. This book will guide you through common industry practices for software delivery and deployment.Throughout the book, you'll follow the journey of a DevOps team that matures their software release process from quarterly deployments to continuous delivery using GitOps. With the help of hands-on tutorials, projects, and self-assessment questions, you'll build your knowledge of GitOps basics, different types of GitOps practices, and how to decide which GitOps practice is the best for your company. As you progress, you'll cover everything from building declarative language files to the pitfalls in performing continuous deployment with GitOps.By the end of this book, you'll be well-versed with the fundamentals of delivery and deployment, the different schools of GitOps, and how to best leverage GitOps in your teams.
Dipti Chhatrapati, Dipti Chhatrapati, Bjoern Rapp
Svetlana Karslioglu
Pachyderm is an open source project that enables data scientists to run reproducible data pipelines and scale them to an enterprise level. This book will teach you how to implement Pachyderm to create collaborative data science workflows and reproduce your ML experiments at scale.You’ll begin your journey by exploring the importance of data reproducibility and comparing different data science platforms. Next, you’ll explore how Pachyderm fits into the picture and its significance, followed by learning how to install Pachyderm locally on your computer or a cloud platform of your choice. You’ll then discover the architectural components and Pachyderm's main pipeline principles and concepts. The book demonstrates how to use Pachyderm components to create your first data pipeline and advances to cover common operations involving data, such as uploading data to and from Pachyderm to create more complex pipelines. Based on what you've learned, you'll develop an end-to-end ML workflow, before trying out the hyperparameter tuning technique and the different supported Pachyderm language clients. Finally, you’ll learn how to use a SaaS version of Pachyderm with Pachyderm Notebooks.By the end of this book, you will learn all aspects of running your data pipelines in Pachyderm and manage them on a day-to-day basis.
