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Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results
Leverage Azure Pipelines to build, test, monitor, and deploy CI/CD solutions on Azure, AWS, and Flutter mobile apps while integrating with tools like Jenkins and SonarQube using best practices Key Features Develop automated end-to-end CI/CD solutions with Azure Pipelines Learn how to implement and configure your pipeline using real-world examples and scenarios Gain the skills you need to efficiently develop and deploy your organization’s software Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionContinuous integration and continuous delivery (CI/CD) are ubiquitous concepts in modern development. Azure Pipelines is one of the most popular services that you can utilize for CI/CD, and this book shows you how it works by taking you through the process of building and automating CI/CD systems using Azure Pipelines and YAML, simplifying integration with Azure resources and reducing human error. You’ll begin by getting an overview of Azure Pipelines and why you should use it. Next, the book helps you get to grips with build and release pipelines, and then builds upon this by introducing the extensive power of YAML syntax, which you can use to implement and configure any task you can think of. As you advance, you’ll discover how to integrate Infrastructure as Code tools, such as Terraform, and perform code analysis with SonarQube. In the concluding chapters, you’ll delve into real-life scenarios and hands-on implementation tasks with Microsoft Azure services, AWS, and cross-mobile application with Flutter, Google Firebase, and more. By the end of this book, you’ll be able to design and build CI/CD systems using Azure Pipelines with consummate ease, write code using YAML, and configure any task that comes to mind.What you will learn Create multiple jobs, stages, and tasks on the Azure DevOps portal Use YAML syntax for Node.js, .NET, Docker, and SQL Server tasks Automate microservice applications on Azure Kubernetes Service (AKS) clusters Deploy Docker applications on AWS container services Use SonarQube and Jenkins for security and artifacts Implement CI/CD on Flutter-based mobile applications Utilize Azure Key Vault secrets in Azure Pipelines Build a Node.js application in Azure Container Instances Who this book is for This book is for DevOps engineers, release engineers, SREs, application developers, and sysadmins looking to manage CI/CD using Azure Pipelines with the help of real-world use cases. A clear understanding of cloud computing services on Azure and AWS, DevOps, and CI/CD concepts, along with knowledge of building and deploying web and mobile applications automatically on cloud is assumed.
The low cost of getting started with cloud services can easily evolve into a significant expense down the road. That's challenging for teams developing data pipelines, particularly when rapid changes in technology and workload require a constant cycle of redesign. How do you deliver scalable, highly available products while keeping costs in check? With this practical guide, author Sev Leonard provides a holistic approach to designing scalable data pipelines in the cloud. Intermediate data engineers, software developers, and architects will learn how to navigate cost/performance trade-offs and how to choose and configure compute and storage. You'll also pick up best practices for code development, testing, and monitoring. By focusing on the entire design process, you'll be able to deliver cost-effective, high-quality products. This book helps you: Reduce cloud spend with lower cost cloud service offerings and smart design strategies Minimize waste without sacrificing performance by rightsizing compute resources Drive pipeline evolution, head off performance issues, and quickly debug with effective monitoring Set up development and test environments that minimize cloud service dependencies Create data pipeline code bases that are testable and extensible, fostering rapid development and evolution Improve data quality and pipeline operation through validation and testing
Indigenous peoples have suffered disproportionately from the effects of extractive industries on their lands and livelihoods, including environmental degradation, human rights violations, and dispossession. Although the abuses have been ongoing, there has been a growing assertion of the rights of indigenous peoples to decide their own development paths, which frequently calls for the rejection of large-scale extractive projects. Based primarily on the proceedings of an International Conference on Extractive Industries and Indigenous Peoples that took place in Manila in March 2009, this book thematically explores the nature of the problem, reviews recent developments and analyses the strategies employed at local, national, and international levels.
Develop production-ready ETL pipelines by leveraging Python libraries and deploying them for suitable use cases Key Features Understand how to set up a Python virtual environment with PyCharm Learn functional and object-oriented approaches to create ETL pipelines Create robust CI/CD processes for ETL pipelines Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionModern extract, transform, and load (ETL) pipelines for data engineering have favored the Python language for its broad range of uses and a large assortment of tools, applications, and open source components. With its simplicity and extensive library support, Python has emerged as the undisputed choice for data processing. In this book, you’ll walk through the end-to-end process of ETL data pipeline development, starting with an introduction to the fundamentals of data pipelines and establishing a Python development environment to create pipelines. Once you've explored the ETL pipeline design principles and ET development process, you'll be equipped to design custom ETL pipelines. Next, you'll get to grips with the steps in the ETL process, which involves extracting valuable data; performing transformations, through cleaning, manipulation, and ensuring data integrity; and ultimately loading the processed data into storage systems. You’ll also review several ETL modules in Python, comparing their pros and cons when building data pipelines and leveraging cloud tools, such as AWS, to create scalable data pipelines. Lastly, you’ll learn about the concept of test-driven development for ETL pipelines to ensure safe deployments. By the end of this book, you’ll have worked on several hands-on examples to create high-performance ETL pipelines to develop robust, scalable, and resilient environments using Python.What you will learn Explore the available libraries and tools to create ETL pipelines using Python Write clean and resilient ETL code in Python that can be extended and easily scaled Understand the best practices and design principles for creating ETL pipelines Orchestrate the ETL process and scale the ETL pipeline effectively Discover tools and services available in AWS for ETL pipelines Understand different testing strategies and implement them with the ETL process Who this book is for If you are a data engineer or software professional looking to create enterprise-level ETL pipelines using Python, this book is for you. Fundamental knowledge of Python is a prerequisite.
Your take-action guide to gender equity First, just to be clear: Leading While Female is not a book about how to get a leadership job. Nor is it about fixing or transforming women into male managers or mindsets. Instead, Arriaga, Stanley, and Lindsey’s bigger ambition is to help both women and men educational leaders confront and close the gender equity gap—a gap that currently denies highly qualified women and women of color opportunities to better serve our millions of public school students. Designed as both a personal and group discussion guide for taking action, Leading While Female draws on the research of feminism, intersectionality, educational leadership, and Cultural Proficiency to help us all: Better understand the impact of faux narratives that foster lack of confidence among girls and women Utilize the Tools of Cultural Proficiency to examine barriers to overcome and support functions to locate for your own career planning Learn from the stories of women leaders who have confronted and overcome barriers to career development, including women of color who were targets of implicit bias Explore and expand the roles and opportunities for our male colleagues to serve as allies, advocates, and mentors. If we look at the data, we can safely say women are doing the work of classroom teaching while disproportionately, men are making administrative and leadership decisions. Here at last is a resource for the breaking down the barriers and leading the way for future generations of women leaders.
The issues arising from rapid global integration have generally been treated in isolation by most academic works. This volume examines the many pitfalls of globalization from the perspective of impoverished and indigenous peoples, including the widening wealth gap, the struggle for restoration of dispossessed lands and cultural rights, global warming and ecological annihilation, and the experiences of women in underdeveloped regions. The United States' growing prison industrial complex is discussed. The author concludes with a call for reassessing current ways of living and proposes recreating cultures of conservation and sustainable economies. Instructors considering this book for use in a course may request an examination copy here.
Every production is built on the backbone of the pipeline. While a functional and flexible pipeline can’t assure a successful project, a weak pipeline can guarantee its demise. A solid pipeline produces a superior product in less time and with happier artists who can remain creative throughout the grueling production schedule. Walk through the foundational layers of the production pipeline, including IT infrastructure, software development practices and deployment policies, asset management, shot management, and rendering management. Production Pipeline Fundamentals for Film and Games will teach you how to direct limited resources to the right technological initiatives, getting the most for every dollar spent. Learn how to prepare for and manage all aspects of the pipeline with this entirely unique, one-of-a-kind guide. Expand your knowledge with real-world pipeline secrets handed to you by a stellar group of professionals from across the globe. Visit the companion website for even further resources on the pipeline.
Rev. ed. of: Computer organization and design / John L. Hennessy, David A. Patterson. 1998.