Programowanie
Big Data on Kubernetes. A practical guide to building efficient and scalable data solutions
Neylson Crepalde
In today's data-driven world, organizations across different sectors need scalable and efficient solutions for processing large volumes of data. Kubernetes offers an open-source and cost-effective platform for deploying and managing big data tools and workloads, ensuring optimal resource utilization and minimizing operational overhead. If you want to master the art of building and deploying big data solutions using Kubernetes, then this book is for you.Written by an experienced data specialist, Big Data on Kubernetes takes you through the entire process of developing scalable and resilient data pipelines, with a focus on practical implementation. Starting with the basics, you’ll progress toward learning how to install Docker and run your first containerized applications. You’ll then explore Kubernetes architecture and understand its core components. This knowledge will pave the way for exploring a variety of essential tools for big data processing such as Apache Spark and Apache Airflow. You’ll also learn how to install and configure these tools on Kubernetes clusters. Throughout the book, you’ll gain hands-on experience building a complete big data stack on Kubernetes.By the end of this Kubernetes book, you’ll be equipped with the skills and knowledge you need to tackle real-world big data challenges with confidence.
Tiago Antao
Bioinformatics is an active research field that uses a range of simple-to-advanced computations to extract valuable information from biological data.This book covers next-generation sequencing, genomics, metagenomics, population genetics, phylogenetics, and proteomics. You'll learn modern programming techniques to analyze large amounts of biological data. With the help of real-world examples, you'll convert, analyze, and visualize datasets using various Python tools and libraries.This book will help you get a better understanding of working with a Galaxy server, which is the most widely used bioinformatics web-based pipeline system. This updated edition also includes advanced next-generation sequencing filtering techniques. You'll also explore topics such as SNP discovery using statistical approaches under high-performance computing frameworks such as Dask and Spark.By the end of this book, you'll be able to use and implement modern programming techniques and frameworks to deal with the ever-increasing deluge of bioinformatics data.
Shane Brubaker
If you've ever felt overwhelmed by the vast number of Python tools available for bioinformatics, you're not alone. The Bioinformatics with Python Cookbook is a recipe-based guide that explores practical approaches for solving classic bioinformatics challenges, showing you which Python packages work best for each task.You’ll start with the essential Python libraries for data science and bioinformatics, then move through key workflows in sequencing analysis, quality control, alignment, and variant calling. Along the way, you’ll pick up modern coding practices, explore recent advances in bioinformatics research, and gain hands-on experience with libraries such as NumPy, pandas, and sci-kit learn. This book walks you through core bioinformatics tasks such as phylogenetic analysis and population genomics while familiarizing you with the wealth of modern public bioinformatics databases. You’ll learn cloud computing approaches used by researchers, set up workflow orchestration systems for controlling bioinformatics pipelines, and see how AI and the use of large language models (LLMs) are reshaping the field–right down to designing proteins and DNA.By the end of this book, you’ll be ready to apply Python for real bioinformatics work and launch bioinformatics pipelines for your research.
Tiago Antao
Bioinformatics is an active research field that uses a range of simple-to-advanced computations to extract valuable information from biological data, and this book will show you how to manage these tasks using Python.This updated third edition of the Bioinformatics with Python Cookbook begins with a quick overview of the various tools and libraries in the Python ecosystem that will help you convert, analyze, and visualize biological datasets. Next, you'll cover key techniques for next-generation sequencing, single-cell analysis, genomics, metagenomics, population genetics, phylogenetics, and proteomics with the help of real-world examples. You'll learn how to work with important pipeline systems, such as Galaxy servers and Snakemake, and understand the various modules in Python for functional and asynchronous programming. This book will also help you explore topics such as SNP discovery using statistical approaches under high-performance computing frameworks, including Dask and Spark. In addition to this, you’ll explore the application of machine learning algorithms in bioinformatics.By the end of this bioinformatics Python book, you'll be equipped with the knowledge you need to implement the latest programming techniques and frameworks, empowering you to deal with bioinformatics data on every scale.
Darko Medin
This book leverages the author’s decade-long experience in biostatistics and data science to simplify the practical use of biostatistics with Python. The chapters show you how to clean and describe your data effectively, setting a solid foundation for accurate analysis and proficiency in biostatistical inference to help you draw meaningful conclusions from your data through hypothesis testing and effect size analysis.The book walks you through predictive modeling to harness the power of Python to create robust predictive analytics that can drive your research and professional projects forward. You'll explore clinical biostatistics, learn how to design studies, conduct survival analysis, and synthesize evidence from multiple studies with meta-analysis – skills that are crucial for making informed decisions based on comprehensive data reviews. The concluding chapters will enhance your ability to analyze biological variables, enabling you to perform detailed and accurate data analysis for biological research. This book's unique blend of biostatistics and Python helps you find practical solutions that make complex concepts easy to grasp and apply.By the end of this biostatistics book, you’ll have moved from theoretical knowledge to practical experience, allowing you to perform biostatistical analysis confidently and accurately.
Albert Szmigielski
Blockchain is being billed as the technology of the future. Bitcoin is the first application of that technology. Mining is what makes it all possible. Exploring mining from a practical perspective will help you make informed decisions about your mining setup. Understanding what the future may hold for blockchains, and therefore for mining, will help you position yourself to take advantage of the impending changes.This practical guide starts with an introduction to Bitcoin wallets, as well as mining hardware and software. You will move on to learn about different mining techniques using the CPU, GPU, FPGA, and ultimately the ASIC as an example. After this, you will gain an insight into solo mining and pool mining, and see the differences between the two. The book will then walk you through large-scale mining and the challenges faced during such operations. Finally, you will take a look into the future to see a world where blockchain-based applications are commonplace and mining is ubiquitous.
Pawel Bazyluk
With support for both server-side and client-side hosting, as well as the flexibility to mix render modes, Blazor empowers you to leverage cloud computing while maintaining the performance of local applications. Paweł Bazyluk—a Blazor expert with over a decade of experience in .NET technologies—shows you how Blazor, a Microsoft framework, enables you to create interactive web applications using C# and .NET, while reducing reliance on JavaScript. This cookbook highlights Blazor’s vast possibilities using practical recipes that address key aspects of web development and showcase the framework's versatility in building modern, integrated applications.Pawel demonstrates how to skillfully navigate component-based architecture, and create, parameterize, and customize components to achieve high modularity. Working through practical insights and hands-on guidance in each chapter, you’ll progress from advanced data binding and event handling intricacies to optimizing data display using grids. You’ll explore application state management, build interactive forms with validation, leverage Blazor’s routing engine, and keep every part of the application secure. The book also explores cutting-edge topics, touching on how to enhance your application with AI-powered features.By the end of the book, you’ll be fully equipped to build robust, scalable, and secure web applications in Blazor.
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#.