• SwiftUI Views Jumpstart 2019-10-29.pdf

    Master SwiftUI View It shows you the biggest conceptual and code changes that can make SwiftUI difficult to learn, if not known.

    2019-11-10
    9
  • Mastering Vim

    Mastering Vim, reviewed by Bram Moolenaar, the creator of Vim, covers usage of Vim and Neovim, showcases relevant plugins, and teaches Vimscript Key Features Expert Vim and Vimscript techniques to work with Python and other development environment Accomplish end-to-end software development tasks with Neovim and Vim plugins Understand best practices for various facets of projects like version control, building, and testing Book Description Vim is a ubiquitous text editor that can be used for all programming languages. It has an extensive plugin system and integrates with many tools. Vim offers an extensible and customizable development environment for programmers, making it one of the most popular text editors in the world. Mastering Vim begins with explaining how the Vim editor will help you build applications efficiently. With the fundamentals of Vim, you will be taken through the Vim philosophy. As you make your way through the chapters, you will learn about advanced movement, text operations, and how Vim can be used as a Python (or any other language for that matter) IDE. The book will then cover essential tasks, such as refactoring, debugging, building, testing, and working with a version control system, as well as plugin configuration and management. In the concluding chapters, you will be introduced to additional mindset guidelines, learn to personalize your Vim experience, and go above and beyond with Vimscript.

    2018-12-25
    27
  • Testing Microservices with Mountebank

    微服务测试 Microservices are independent, single-responsibility units of code that form a system with other microservices. It's difficult to test an individual microservice since each one depends on the other services. Mountebank solves this conundrum through service virtualization - imitating other components in the system so that you can test a microservice in isolation.

    2018-12-25
    12
  • Learn by Example: JavaScript for Front-End and Mobile App Development

    This book aims to take someone completely new to programming all the way from beginner to advanced. The book starts by covering the basic syntax required to get up and running with web development, and then moves onto advanced concepts and examples. Each section takes the reader along in an intuitive and easy to follow step-by-step manner with clear color images and screenshots, all the way from newbie to advanced. Practical Examples and Assignments Each section contains practical examples and assignments that help the reader understand concepts and practice code. Finally! an easy way to make mobile apps Instead of learning Swift for ios and Java for Android, just learn JavaScript and make apps for ALL platforms using Apache Cordova. This book also covers everything you need to know in order to use JavaScript to design, develop, and deploy mobile apps. Key Topics Introduction to HTML CSS Basics Advanced CSS styling Introduction to JavaScript Data-types Functions Callbacks The this keyword Get elements from the DOM Building your first mobile app Becoming an app developer Deploying your app to the Android and iTunes app stores

    2018-12-25
    9
  • Machine Learning with AWS

    Use artificial intelligence and machine learning on AWS to create engaging applications Key Features • Explore popular AI and ML services with their underlying algorithms • Use the AWS environment to manage your AI workflow • Reinforce key concepts with hands-on exercises using real-world datasets Book Description Machine Learning with AWS is the right place to start if you are a beginner interested in learning useful artificial intelligence (AI) and machine learning skills using Amazon Web Services (AWS), the most popular and powerful cloud platform. You will learn how to use AWS to transform your projects into apps that work at high speed and are highly scalable. From natural language processing (NLP) applications, such as language translation and understanding news articles and other text sources, to creating chatbots with both voice and text interfaces, you will learn all that there is to know about using AWS to your advantage. You will also understand how to process huge numbers of images fast and create machine learning models. By the end of this book, you will have developed the skills you need to efficiently use AWS in your machine learning and artificial intelligence projects. What you will learn • Get up and running with machine learning on the AWS platform • Analyze unstructured text using AI and Amazon Comprehend • Create a chatbot and interact with it using speech and text input • Retrieve external data via your chatbot • Develop a natural language interface • Apply AI to images and videos with Amazon Rekognition Who this book is for Machine Learning with AWS is ideal for data scientists, programmers, and machine learning enthusiasts who want to learn about the artificial intelligence and machine learning capabilities of Amazon Web Services.

    2018-12-23
    10
  • Mining the Social Web 3rd Edition

    第3版 Mine the rich data tucked away in popular social websites such as Twitter, Facebook, LinkedIn, and Instagram. With the third edition of this popular guide, data scientists, analysts, and programmers will learn how to glean insights from social media—including who’s connecting with whom, what they’re talking about, and where they’re located—using Python code examples, Jupyter notebooks, or Docker containers.

    2018-12-15
    14
  • Pro Spring Boot 2 2nd Edition

    Quickly and productively develop complex Spring applications and microservices out of the box, with minimal concern over things like configurations. This revised book will show you how to fully leverage the Spring Boot 2 technology and how to apply it to create enterprise ready applications that just work. It will also cover what's been added to the new Spring Boot 2 release, including Spring Framework 5 features like WebFlux, Security, Actuator and the new way to expose Metrics through Micrometer framework, and more. This book is your authoritative hands-on practical guide for increasing your enterprise Java and cloud application productivity while decreasing development time. It's a no nonsense guide with case studies of increasing complexity throughout the book. The author, a senior solutions architect and Principal Technical instructor with Pivotal, the company behind the Spring Framework, shares his experience, insights and first-hand knowledge about how Spring Boot technology works and best practices. Pro Spring Boot 2 is an essential book for your Spring learning and reference library.

    2018-12-15
    9
  • Agile for Everybody

    The Agile movement provides real, actionable answers to the question that keeps many company leaders awake at night: How do we stay successful in a fast-changing and unpredictable world? Agile has already transformed how modern companies build and deliver software. This practical book demonstrates how entire organizations—from product managers and engineers to marketers and executives—can put Agile to work. Author Matt LeMay explains Agile in clear, jargon-free terms and provides concrete and actionable steps to help any team put its values and principles into practice. Examples from a wide variety of organizations, including small nonprofits and global financial enterprises, bring to life the on-the-ground realities of Agile across industries and functions. • Understand exactly what Agile is and why it matters • Use Agile to address your organization’s specific needs and goals • Take customer centricity from theory into practice • Stop wasting time in "report and critique" meetings and start making better decisions • Create a harmonious cycle of learning, collaborating, and delivering • Learn from Agile experts at companies like IBM, Spotify, and Coca-Cola

    2018-12-12
    10
  • Migrating to MariaDB: Toward an Open Source Database Solution

    Mitigate the risks involved in migrating away from a proprietary database platform toward MariaDB’s open source database engine. This book will help you assess the risks and the work involved, and ensure a successful migration. Migrating to MariaDB describes the process and lessons learned during a migration from a proprietary database management engine to the MariaDB open source solution. The book discusses the drivers for making the decision and change, walking you through all aspects of the process from evaluating the licensing, navigating the pitfalls and hurdles of a migration, through to final implementation on the new platform. The book highlights the cost-effectiveness of MariaDB and how the licensing worries are simplified in comparison to running on a proprietary platform. You’ll learn to do your own risk assessment, to identify database and application code that may need to be modified or re-implemented, and to identify MariaDB features to provide the security and failover protection needed by corporate customers. Let the author’s experience in migrating a financial firm to MariaDB inform your own efforts, helping you to develop a road map for both technical and political success within your own organization as you migrate away from proprietary lock-in toward MariaDB’s open source solution.

    2018-12-10
    10
  • Learn Keras for Deep Neural Networks

    Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use-cases implemented in Keras. The overall book comprises three sections with two chapters in each section. The first section prepares you with all the necessary basics to get started in deep learning. Chapter 1 introduces you to the world of deep learning and its difference from machine learning, the choices of frameworks for deep learning, and the Keras ecosystem. You will cover a real-life business problem that can be solved by supervised learning algorithms with deep neural networks. You’ll tackle one use case for regression and another for classification leveraging popular Kaggle datasets. Later, you will see an interesting and challenging part of deep learning: hyperparameter tuning; helping you further improve your models when building robust deep learning applications. Finally, you’ll further hone your skills in deep learning and cover areas of active development and research in deep learning. At the end of Learn Keras for Deep Neural Networks, you will have a thorough understanding of deep learning principles and have practical hands-on experience in developing enterprise-grade deep learning solutions in Keras.

    2018-12-10
    6
关注 私信
上传资源赚积分or赚钱