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Podcasts
Refactoring in Java. Improving code design and maintainability for Java developers
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.
Onur Yilmaz, Sathsara Sarathchandra
Kubernetes has established itself as the standard platform for container management, orchestration, and deployment. By learning Kubernetes, you’ll be able to design your own serverless architecture by implementing the function-as-a-service (FaaS) model.After an accelerated, hands-on overview of the serverless architecture and various Kubernetes concepts, you’ll cover a wide range of real-world development challenges faced by real-world developers, and explore various techniques to overcome them. You’ll learn how to create production-ready Kubernetes clusters and run serverless applications on them. You'll see how Kubernetes platforms and serverless frameworks such as Kubeless, Apache OpenWhisk and OpenFaaS provide the tooling to help you develop serverless applications on Kubernetes. You'll also learn ways to select the appropriate framework for your upcoming project. By the end of this book, you’ll have the skills and confidence to design your own serverless applications using the power and flexibility of Kubernetes.
Desktop virtualization can be tough, but VMware Horizon 7.8 changes all that. With a rich and adaptive UX, improved security,and a range of useful features for storage and networking optimization, there's plenty to love.But to properly fall in love with it, you need to know how to use it, and that means venturing deeper into the software and taking advantage of its extensive range of features, many of which are underused and underpromoted. This guide will take you through everything you need to know to not only successfully virtualize your desktop infrastructure, but also to maintain and optimize it to keep all your users happy.We'll show you how to assess and analyze your infrastructure, and how to use that analysis to design a solution that meets your organizational and user needs. Once you've done that, you'll find out how to build your virtualized environment, before deploying your virtualized solution. But more than that,we'll also make sure you know everything you need to know about the full range of features on offer, including the mobile cloud, so that you can use them to take full control of your virtualized infrastructure.
R: Predictive Analysis. Master the art of predictive modeling
Eric Mayor, Tony Fischetti, Rui Miguel Forte
Predictive analytics is a field that uses data to build models that predict a future outcome of interest. It can be applied to a range of business strategies and has been a key player in search advertising and recommendation engines.The power and domain-specificity of R allows the user to express complex analytics easily, quickly, and succinctly. R offers a free and open source environment that is perfect for both learning and deploying predictive modeling solutions in the real world. This Learning Path will provide you with all the steps you need to master the art of predictive modeling with R. We start with an introduction to data analysis with R, and then gradually you’ll get your feet wet with predictive modeling. You will get to grips with the fundamentals of applied statistics and build on this knowledge to perform sophisticated and powerful analytics. You will be able to solve the difficulties relating to performing data analysis in practice and find solutions to working with “messy data”, large data, communicating results, and facilitating reproducibility. You will then perform key predictive analytics tasks using R, such as train and test predictive models for classification and regression tasks, score new data sets and so on. By the end of this Learning Path, you will have explored and tested the most popular modeling techniques in use on real-world data sets and mastered a diverse range of techniques in predictive analytics.This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products:• Data Analysis with R, Tony Fischetti• Learning Predictive Analytics with R, Eric Mayor• Mastering Predictive Analytics with R, Rui Miguel Forte
Fanny Ip, Jeremiah Crowley, Tom Torlone
Artificial intelligence (AI) enables enterprises to optimize business processes that are probabilistic, highly variable, and require cognitive abilities with unstructured data. Many believe there is a steep learning curve with AI, however, the goal of our book is to lower the barrier to using AI. This practical guide to AI with UiPath will help RPA developers and tech-savvy business users learn how to incorporate cognitive abilities into business process optimization. With the hands-on approach of this book, you'll quickly be on your way to implementing cognitive automation to solve everyday business problems.Complete with step-by-step explanations of essential concepts, practical examples, and self-assessment questions, this book will help you understand the power of AI and give you an overview of the relevant out-of-the-box models. You’ll learn about cognitive AI in the context of RPA, the basics of machine learning, and how to apply cognitive automation within the development lifecycle. You’ll then put your skills to test by building three use cases with UiPath Document Understanding, UiPath AI Center, and Druid.By the end of this AI book, you'll be able to build UiPath automations with the cognitive capabilities of intelligent document processing, machine learning, and chatbots, while understanding the development lifecycle.