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Podcasty
Blockchain is a technology that powers the development of decentralized applications.This technology allows the construction of a network with no single control that enables participants to make contributions to and receive benefits from the network directly.This book will give you a thorough overview of blockchain and explain how a blockchain works.You will begin by going through various blockchain consensus mechanisms and cryptographic hash functions. You will then learn the fundamentals of programming in Solidity – the defacto language for developing decentralize, applications in Ethereum. After that, you will set up an Ethereum development environment and develop, package, build, and test campaign-decentralized applications.The book also shows you how to set up Hyperledger composer tools, analyze business scenarios, design business models, and write a chain code. Finally, you will get a glimpse of how blockchain is actually used in different real-world domains. By the end of this guide, you will be comfortable working with basic blockchain frameworks, and develop secure, decentralized applications in a hassle-free manner.
PHP 7 Data Structures and Algorithms. Implement linked lists, stacks, and queues using PHP
PHP has always been the the go-to language for web based application development, but there are materials and resources you can refer to to see how it works. Data structures and algorithms help you to code and execute them effectively, cutting down on processing time significantly.If you want to explore data structures and algorithms in a practical way with real-life projects, then this book is for you.The book begins by introducing you to data structures and algorithms and how to solve a problem from beginning to end using them. Once you are well aware of the basics, it covers the core aspects like arrays, listed lists, stacks and queues. It will take you through several methods of finding efficient algorithms and show you which ones you should implement in each scenario. In addition to this, you will explore the possibilities of functional data structures using PHP and go through advanced algorithms and graphs as well as dynamic programming. By the end, you will be confident enough to tackle both basic and advanced data structures, understand how they work, and know when to use them in your day-to-day work
Michael Hackett, Vikhyat Umrao, Karan Singh, Nick Fisk, ...
This Learning Path takes you through the basics of Ceph all the way to gaining in-depth understanding of its advanced features. You’ll gather skills to plan, deploy, and manage your Ceph cluster. After an introduction to the Ceph architecture and its core projects, you’ll be able to set up a Ceph cluster and learn how to monitor its health, improve its performance, and troubleshoot any issues. By following the step-by-step approach of this Learning Path, you’ll learn how Ceph integrates with OpenStack, Glance, Manila, Swift, and Cinder. With knowledge of federated architecture and CephFS, you’ll use Calamari and VSM to monitor the Ceph environment. In the upcoming chapters, you’ll study the key areas of Ceph, including BlueStore, erasure coding, and cache tiering. More specifically, you’ll discover what they can do for your storage system. In the concluding chapters, you will develop applications that use Librados and distributed computations with shared object classes, and see how Ceph and its supporting infrastructure can be optimized. By the end of this Learning Path, you'll have the practical knowledge of operating Ceph in a production environment.This Learning Path includes content from the following Packt products:• Ceph Cookbook by Michael Hackett, Vikhyat Umrao and Karan Singh• Mastering Ceph by Nick Fisk• Learning Ceph, Second Edition by Anthony D'Atri, Vaibhav Bhembre and Karan Singh
Moodle 3.x Developer's Guide. Build custom plugins, extensions, modules and more
The new and revamped Moodle is the top choice for developers to create cutting edge e-learning apps that cater to different user’s segments and are visually appealing as well. This book explains how the Moodle 3.x platform provides a framework that allows developers to create a customized e-learning solution. It begins with an exploration of the different types of plugin.. We then continue with an investigation of creating new courses. You will create a custom plugin that pulls in resources from a third-party repository. Then you’ll learn how users can be assigned to courses and granted the necessary permissions.Furthermore, you will develop a custom user home. At the end of the book, we’ll discuss the Web Services API to fully automate Moodle 3.x in real time.
James Lee, Tao Wei, Suresh Kumar Mukhiya
Modeling and managing data is a central focus of all big data projects. In fact, a database is considered to be effective only if you have a logical and sophisticated data model. This book will help you develop practical skills in modeling your own big data projects and improve the performance of analytical queries for your specific business requirements.To start with, you’ll get a quick introduction to big data and understand the different data modeling and data management platforms for big data. Then you’ll work with structured and semi-structured data with the help of real-life examples. Once you’ve got to grips with the basics, you’ll use the SQL Developer Data Modeler to create your own data models containing different file types such as CSV, XML, and JSON. You’ll also learn to create graph data models and explore data modeling with streaming data using real-world datasets.By the end of this book, you’ll be able to design and develop efficient data models for varying data sizes easily and efficiently.
Docker and Kubernetes for Java Developers. Scale, deploy, and monitor multi-container applications
Imagine creating and testing Java EE applications on Apache Tomcat Server or Wildfly Application server in minutes along with deploying and managing Java applications swiftly. Sounds too good to be true? But you have a reason to cheer as such scenarios are only possible by leveraging Docker and Kubernetes.This book will start by introducing Docker and delve deep into its networking and persistent storage concepts. You will then proceed to learn how to refactor monolith application into separate services by building an application and then packaging it into Docker containers. Next, you will create an image containing Java Enterprise Application and later run it using Docker. Moving on, the book will focus on Kubernetes and its features and you will learn to deploy a Java application to Kubernetes using Maven and monitor a Java application in production. By the end of the book, you will get hands-on with some more advanced topics to further extend your knowledge about Docker and Kubernetes.
Getting Started with Terraform. Manage production infrastructure as a code - Second Edition
Terraform is a tool used to efficiently build, configure, and improve the production infrastructure. It can manage the existing infrastructure as well as create custom in-house solutions. This book shows you when and how to implement infrastructure as a code practices with Terraform. It covers everything necessary to set up the complete management of infrastructure with Terraform, starting with the basics of using providers and resources. It is a comprehensive guide that begins with very small infrastructure templates and takes you all the way to managing complex systems, all using concrete examples that evolve over the course of the book. The book ends with the complete workflow of managing a production infrastructure as code—this is achieved with the help of version control and continuous integration. The readers will also learn how to combine multiple providers in a single template and manage different code bases with many complex modules. It focuses on how to set up continuous integration for the infrastructure code.The readers will be able to use Terraform to build, change, and combine infrastructure safely and efficiently.
Apache Spark is an open source framework for efficient cluster computing with a strong interface for data parallelism and fault tolerance. The PySpark Cookbook presents effective and time-saving recipes for leveraging the power of Python and putting it to use in the Spark ecosystem.You’ll start by learning the Apache Spark architecture and how to set up a Python environment for Spark. You’ll then get familiar with the modules available in PySpark and start using them effortlessly. In addition to this, you’ll discover how to abstract data with RDDs and DataFrames, and understand the streaming capabilities of PySpark. You’ll then move on to using ML and MLlib in order to solve any problems related to the machine learning capabilities of PySpark and use GraphFrames to solve graph-processing problems. Finally, you will explore how to deploy your applications to the cloud using the spark-submit command.By the end of this book, you will be able to use the Python API for Apache Spark to solve any problems associated with building data-intensive applications.
Giuseppe Ciaburro, Prateek Joshi
This eagerly anticipated second edition of the popular Python Machine Learning Cookbook will enable you to adopt a fresh approach to dealing with real-world machine learning and deep learning tasks.With the help of over 100 recipes, you will learn to build powerful machine learning applications using modern libraries from the Python ecosystem. The book will also guide you on how to implement various machine learning algorithms for classification, clustering, and recommendation engines, using a recipe-based approach. With emphasis on practical solutions, dedicated sections in the book will help you to apply supervised and unsupervised learning techniques to real-world problems. Toward the concluding chapters, you will get to grips with recipes that teach you advanced techniques including reinforcement learning, deep neural networks, and automated machine learning.By the end of this book, you will be equipped with the skills you need to apply machine learning techniques and leverage the full capabilities of the Python ecosystem through real-world examples.
Building RESTful Web Services with PHP 7. Lumen, Composer, API testing, Microservices, and more
REST is the most wide spread and effective standard to develop APIs for internet services. With the way PHP and its eco-system has modernized the way code is written by simplifying various operations, it is useful to develop RESTful APIs with PHP 7 and modern tools.This book explains in detail how to create your own RESTful API in PHP 7 that can be consumed by other users in your organization. Starting with a brief introduction to the fundamentals of REST architecture and the new features in PHP 7, you will learn to implement basic RESTful API endpoints using vanilla PHP. The book explains how to identify flaws in security and design and teach you how to tackle them. You will learn about composer, Lumen framework and how to make your RESTful API cleaner, secure and efficient. The book emphasizes on automated tests, teaches about different testing types and give a brief introduction to microservices which is the natural way forward. After reading this book, you will have a clear understanding of the REST architecture and you can build a web service from scratch.
This book guides developers to create robust, production-ready C# 7 and .NET Core applications through the practice of test-driven development process. In C# and .NET Core Test-Driven Development, you will learn the different stages of the TDD life cycle, basics of TDD, best practices, and anti-patterns. It will teach you how to create an ASP.NET Core MVC sample application, write testable code with SOLID principles and set up a dependency injection for your sample application. Next, you will learn the xUnit testing framework and learn how to use its attributes and assertions. You’ll see how to create data-driven unit tests and mock dependencies in your code. You will understand the difference between running and debugging your tests on .NET Core on LINUX versus Windows and Visual Studio. As you move forward, you will be able to create a healthy continuous integration process for your sample application using GitHub, TeamCity, Cake, and Microsoft VSTS.By the end of this book, you will have learned how to write clean and robust code through the effective practice of TDD, set up CI build steps to test and build applications as well as how to package application for deployment on NuGet.
Karthikeyan NG, Arun Padmanabhan, Matt R. Cole
We’re witnessing a revolution in Artificial Intelligence, thanks to breakthroughs in deep learning. Mobile Artificial Intelligence Projects empowers you to take part in this revolution by applying Artificial Intelligence (AI) techniques to design applications for natural language processing (NLP), robotics, and computer vision.This book teaches you to harness the power of AI in mobile applications along with learning the core functions of NLP, neural networks, deep learning, and mobile vision. It features a range of projects, covering tasks such as real-estate price prediction, recognizing hand-written digits, predicting car damage, and sentiment analysis. You will learn to utilize NLP and machine learning algorithms to make applications more predictive, proactive, and capable of making autonomous decisions with less human input. In the concluding chapters, you will work with popular libraries, such as TensorFlow Lite, CoreML, and PyTorch across Android and iOS platforms.By the end of this book, you will have developed exciting and more intuitive mobile applications that deliver a customized and more personalized experience to users.
Thinking about adapting the DevOps culture for your organization using a very simple, yet powerful automation tool, Ansible 2? Then this book is for you!In this book, you will start with the role of Ansible in the DevOps module, which covers fundamental DevOps practices and how Ansible is leveraged by DevOps organizations to implement consistent and simplified configuration management and deployment. You will then move on to the next module, Ansible with DevOps, where you will understand Ansible fundamentals and how Ansible Playbooks can be used for simple configuration management and deployment tasks. After simpler tasks, you will move on to the third module, Ansible Syntax and Playbook Development, where you will learn advanced configuration management implementations, and use Ansible Vault to secure top-secret information in your organization. In this module, you will also learn about popular DevOps tools and the support that Ansible provides for them (MYSQL, NGINX, APACHE and so on). The last module, Scaling Ansible for the enterprise, is where you will integrate Ansible with CI and CD solutions and provision Docker containers using Ansible.By the end of the book you will have learned to use Ansible to leverage your DevOps tasks.
As one of the more versatile programming languages, Python is well-known for its batteries-included philosophy, which includes a rich set of modules in its standard library; Tkinter is the library included for building desktop applications. Due to this, Tkinter is a common choice for rapid GUI development, and more complex applications can benefit from the full capabilities of this library. This book covers all of your Tkinter and Python GUI development problems and solutions.Tkinter GUI Application Development Cookbook starts with an overview of Tkinter classes and at the same time provides recipes for basic topics, such as layout patterns and event handling. Next, we cover how to develop common GUI patterns, such as entering and saving data, navigating through menus and dialogs, and performing long-running actions in the background.You can then make your apps leverage network resources effectively and perform graphical operations on a canvas and related tasks such as detecting collisions between items. Finally, this book covers using themed widgets, an extension of Tk widgets that have a more native look and feel. Finally, this book covers using the canvas and themed widgets.By the end of the book, you will have an in-depth knowledge of Tkinter classes, and will know how to use them to build efficient and rich GUI applications.
Object-oriented programming (OOP) is a programming paradigm organized around objects rather than actions, and data rather than logic. With the latest release of C#, you can look forward to new additions that improve object-oriented programming. This book will get you up to speed with OOP in C# in an engaging and interactive way. The book starts off by introducing you to C# language essentials and explaining OOP concepts through simple programs. You will then go on to learn how to use classes, interfacesm and properties to write pure OOP code in your applications. You will broaden your understanding of OOP further as you delve into some of the advanced features of the language, such as using events, delegates, and generics. Next, you will learn the secrets of writing good code by following design patterns and design principles. You'll also understand problem statements with their solutions and learn how to work with databases with the help of ADO.NET. Further on, you'll discover a chapter dedicated to the Git version control system. As you approach the conclusion, you'll be able to work through OOP-specific interview questions and understand how to tackle them. By the end of this book, you will have a good understanding of OOP with C# and be able to take your skills to the next level.
Deep Learning with TensorFlow. Explore neural networks with Python
Giancarlo Zaccone, Md. Rezaul Karim, Ahmed Menshawy
Deep learning is the step that comes after machine learning, and has more advancedimplementations. Machine learning is not just for academics anymore, but is becoming a mainstream practice through wide adoption, and deep learning has taken the front seat. As a data scientist, if you want to explore data abstraction layers, this book will be your guide. This book shows how this can be exploited in the real world with complex raw data using TensorFlow 1.x.Throughout the book, you’ll learn how to implement deep learning algorithms for machine learning systems and integrate them into your product offerings, includingsearch, image recognition, and language processing. Additionally, you’ll learn howto analyze and improve the performance of deep learning models. This can be done bycomparing algorithms against benchmarks, along with machine intelligence, to learnfrom the information and determine ideal behaviors within a specific context.After finishing the book, you will be familiar with machine learning techniques, in particular the use of TensorFlow for deep learning, and will be ready to apply your knowledge to research or commercial projects.