Hands-On Blockchain for Python Developers. Gain blockchain programming skills to build decentralized applications using Python

Arjuna Sky Kok

Blockchain is seen as the main technological solution that works as a public ledger for all cryptocurrency transactions. This book serves as a practical guide to developing a full-fledged decentralized application with Python to interact with the various building blocks of blockchain applications.Hands-On Blockchain for Python Developers starts by demonstrating how blockchain technology and cryptocurrency hashing works. You will understand the fundamentals and benefits of smart contracts such as censorship resistance and transaction accuracy. As you steadily progress, you'll go on to build smart contracts using Vyper, which has a similar syntax to Python. This experience will further help you unravel the other benefits of smart contracts, including reliable storage and backup, and efficiency. You'll also use web3.py to interact with smart contracts and leverage the power of both the web3.py and Populus framework to build decentralized applications that offer security and seamless integration with cryptocurrencies. As you explore later chapters, you'll learn how to create your own token on top of Ethereum and build a cryptocurrency wallet graphical user interface (GUI) that can handle Ethereum and Ethereum Request for Comments (ERC-20) tokens using the PySide2 library. This will enable users to seamlessly store, send, and receive digital money. Toward the end, you'll implement InterPlanetary File System (IPFS) technology in your decentralized application to provide a peer-to-peer filesystem that can store and expose media.By the end of this book, you'll be well-versed in blockchain programming and be able to build end-to-end decentralized applications on a range of domains using Python.

Hands-On C++ Game Animation Programming. Learn modern animation techniques from theory to implementation with C++ and OpenGL

Gabor Szauer

Animation is one of the most important parts of any game. Modern animation systems work directly with track-driven animation and provide support for advanced techniques such as inverse kinematics (IK), blend trees, and dual quaternion skinning.This book will walk you through everything you need to get an optimized, production-ready animation system up and running, and contains all the code required to build the animation system. You’ll start by learning the basic principles, and then delve into the core topics of animation programming by building a curve-based skinned animation system. You’ll implement different skinning techniques and explore advanced animation topics such as IK, animation blending, dual quaternion skinning, and crowd rendering. The animation system you will build following this book can be easily integrated into your next game development project. The book is intended to be read from start to finish, although each chapter is self-contained and can be read independently as well.By the end of this book, you’ll have implemented a modern animation system and got to grips with optimization concepts and advanced animation techniques.

Hands-On Chatbot Development with Alexa Skills and Amazon Lex. Create custom conversational and voice interfaces for your Amazon Echo devices and web platforms

Sam Williams

Have you ever wondered how Alexa apps are made, how voice-enabled technologies work, or how chatbots function? And why tech giants such as Amazon and Google are investing in voice technologies? A better question is: why should I start developing on these platforms? Hands-On Chatbot Development with Alexa Skills and Amazon Lex covers all features of the Alexa Skills kit with real-world examples that help you develop skills to integrate Echo and chatbots into Facebook, Slack, and Twilio with the Amazon Lex platform.The book starts with teaching you how to set up your local environment and AWS CLI so that you can automate the process of uploading AWS Lambda from your local machine. You will then learn to develop Alexa Skills and Lex chatbots using Lambda functions to control functionality. Once you’ve come to grips with this, you will learn to create increasingly complex chatbots, integrate Amazon S3, and change the way Alexa talks to the user. In the concluding chapters, we shift our focus to Amazon Lex and messaging chatbots. We will explore Alexa, learn about DynamoDB databases, and add cards to user conversations.By the end of this book, you will have explored a full set of technologies that will enable you to create your own voice and messaging chatbots using Amazon.

Hands-On Chatbots and Conversational UI Development. Build chatbots and voice user interfaces with Chatfuel, Dialogflow, Microsoft Bot Framework, Twilio, and Alexa Skills

Srini Janarthanam

Conversation as an interface is the best way for machines to interact with us using the universally accepted human tool that is language. Chatbots and voice user interfaces are two flavors of conversational UIs. Chatbots are real-time, data-driven answer engines that talk in natural language and are context-aware. Voice user interfaces are driven by voice and can understand and respond to users using speech. This book covers both types of conversational UIs by leveraging APIs from multiple platforms. We'll take a project-based approach to understand how these UIs are built and the best use cases for deploying them. We'll start by building a simple messaging bot from the Facebook Messenger API to understand the basics of bot building. Then we move on to creating a Task model that can perform complex tasks such as ordering and planning events with the newly-acquired-by-Google Dialogflow and Microsoft Bot framework. We then turn to voice-enabled UIs that are capable of interacting with users using speech with Amazon Alexa and Google Home. By the end of the book, you will have created your own line of chatbots and voice UIs for multiple leading platforms.

Hands-On Cloud Administration in Azure. Implement, monitor, and manage important Azure services and components including IaaS and PaaS

Mustafa Toroman

Azure continues to dominate the public cloud market and grow rapidly thanks to a number of recent innovations. Azure's wide range of services and support has led to a large number of customers switching to Azure cloud.Hands-On Cloud Administration in Azure starts with the basics of Azure cloud fundamentals and key concepts of the cloud computing ecosystem and services. Then, you will gradually get acquainted with core services provided by Azure, including Azure VNet, types and assignments of IP addresses, and network security groups. You will also work on creating and administering Azure Virtual Machines, types of virtual machines (VMs), and design VM solutions based on computing workloads. As you make your way through the chapters, you will explore Azure App Service, discover how to host your web apps in Azure, and monitor and troubleshoot them. In the concluding chapters, you will learn more complex and abstract services, such as Azure Storage, Azure Backup, and Azure Site Recovery. You will also get to grips with Azure SQL Databases and the SQL on Azure VM concept.By the end of this book, you will have obtained practical experience of working with Azure services and Azure administration, along with maintaining, monitoring, and securing your Azure resources.

Hands-On Cloud Development with WildFly. Develop, deploy, and configure cloud-based, enterprise Java applications with WildFly Swarm and OpenShift

Tomasz Adamski

The book starts by introducing you to WildFly Swarm—a tool that allows you to create runnable microservices from Java EE components. You’ll learn the basics of Swarm operation—creating microservices containing only the parts of enterprise runtime needed in a specific case. Later, you’ll learn how to configure and test those services.In order to deploy our services in the cloud, we’ll use OpenShift. You’ll get to know basic information on its architecture, features, and relationship to Docker and Kubernetes. Later, you’ll learn how to deploy and configure your services to run in the OpenShift cloud.In the last part of the book, you’ll see how to make your application production-ready. You’ll find out how to configure continuous integration for your services using Jenkins, make your application resistant to network failures using Hystrix, and how to secure them using Keycloak. By the end of the book, you’ll have a functional example application and will have practical knowledge of Java EE cloud development that can be used as a reference in your other projects.

Hands-On Cloud Solutions with Azure. Architecting, developing, and deploying the Azure way

Greg Leonardo

Azure provides cloud-based solutions to support your business demands. Building and running solutions on Azure will help your business maximize the return on investment and minimize the total cost of ownership.Hands-On Cloud Solutions with Azure focuses on addressing the architectural decisions that usually arise when you design or migrate a solution to Microsoft Azure. You will start by designing the building blocks of infrastructure solution on Azure, such as Azure compute, storage, and networking, followed by exploring the database options it offers. You will get to grips with designing scalable web and mobile solutions and understand where to host your Active Directory and Identity Solution. Moving on, you’ll learn how to extend DevOps to Azure.You will also beneft from some exciting services that enable extremely smooth operations and streamlined DevOps between on-premises and cloud. The book will help you to design a secure environment for your solution, on both the Cloud and hybrid. Toward the end, you’ll see how to manage and monitor cloud and hybrid solutions.By the end of this book, you will be armed with all the tools and knowledge you need to properly plan and design your solutions on Azure, whether it’s for a brand new project or migration project.

Hands-On Cloud-Native Applications with Java and Quarkus. Build high performance, Kubernetes-native Java serverless applications

Francesco Marchioni, Mark Little

Quarkus is a new Kubernetes-native framework that allows Java developers to combine the power of containers, microservices, and cloud-native to build reliable applications. The book is a development guide that will teach you how to build Java-native applications using Quarkus and GraalVM.We start by learning about the basic concepts of a cloud-native application and its advantages over standard enterprise applications. Then we will quickly move on to application development, by installing the tooling required to build our first application on Quarkus. Next, we’ll learn how to create a container-native image of our application and execute it in a Platform-as-a-Service environment such as Minishift. Later, we will build a complete real-world application that will use REST and the Contexts and Dependency injection stack with a web frontend. We will also learn how to add database persistence to our application using PostgreSQL. We will learn how to work with various APIs available to?Quarkus?such as Camel, Eclipse MicroProfile, and Spring DI. Towards the end, we will learn advanced development techniques such as securing applications, application configuration, and working with non-blocking programming models using Vert.x.By the end of this book, you will be proficient with all the components of Quarkus and develop-blazing fast applications leveraging modern technology infrastructure.

Hands-On Cloud-Native Microservices with Jakarta EE. Build scalable and reactive microservices with Docker, Kubernetes, and OpenShift

Luigi Fugaro, Mauro Vocale

Businesses today are evolving rapidly, and developers now face the challenge of building applications that are resilient, flexible, and native to the cloud. To achieve this, you'll need to be aware of the environment, tools, and resources that you're coding against. The book will begin by introducing you to cloud-native architecture and simplifying the major concepts. You'll learn to build microservices in Jakarta EE using MicroProfile with Thorntail and Narayana LRA. You'll then delve into cloud-native application x-rays, understanding the MicroProfile specification and the implementation/testing of microservices. As you progress further, you'll focus on continuous integration and continuous delivery, in addition to learning how to dockerize your services. You'll also cover concepts and techniques relating to security, monitoring, and troubleshooting problems that might occur with applications after you've written them.By the end of this book, you will be equipped with the skills you need to build highly resilient applications using cloud-native microservice architecture.

Hands-On Computer Vision with Julia. Build complex applications with advanced Julia packages for image processing, neural networks, and Artificial Intelligence

Dmitrijs Cudihins

Hands-On Computer Vision with Julia is a thorough guide for developers who want to get started with building computer vision applications using Julia. Julia is well suited to image processing because it’s easy to use and lets you write easy-to-compile and efficient machine code..This book begins by introducing you to Julia's image processing libraries such as Images.jl and ImageCore.jl. You’ll get to grips with analyzing and transforming images using JuliaImages; some of the techniques discussed include enhancing and adjusting images. As you make your way through the chapters, you’ll learn how to classify images, cluster them, and apply neural networks to solve computer vision problems. In the concluding chapters, you will explore OpenCV applications to perform real-time computer vision analysis, for example, face detection and object tracking. You will also understand Julia's interaction with Tesseract to perform optical character recognition and build an application that brings together all the techniques we introduced previously to consolidate the concepts learned.By end of the book, you will have understood how to utilize various Julia packages and a few open source libraries such as Tesseract and OpenCV to solve computer vision problems with ease.

Hands-On Computer Vision with TensorFlow 2. Leverage deep learning to create powerful image processing apps with TensorFlow 2.0 and Keras

Benjamin Planche, Eliot Andres

Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. This book will help you explore TensorFlow 2, the brand new version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks.Hands-On Computer Vision with TensorFlow 2 starts with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the book demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative adversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts.By the end of the book, you will have both the theoretical understanding and practical skills to solve advanced computer vision problems with TensorFlow 2.0.

Hands-On Concurrency with Rust. Confidently build memory-safe, parallel, and efficient software in Rust

Brian L. Troutwine

Most programming languages can really complicate things, especially with regard to unsafe memory access. The burden on you, the programmer, lies across two domains: understanding the modern machine and your language's pain-points. This book will teach you to how to manage program performance on modern machines and build fast, memory-safe, and concurrent software in Rust. It starts with the fundamentals of Rust and discusses machine architecture concepts. You will be taken through ways to measure and improve the performance of Rust code systematically and how to write collections with confidence. You will learn about the Sync and Send traits applied to threads, and coordinate thread execution with locks, atomic primitives, data-parallelism, and more.The book will show you how to efficiently embed Rust in C++ code and explore the functionalities of various crates for multithreaded applications. It explores implementations in depth. You will know how a mutex works and build several yourself. You will master radically different approaches that exist in the ecosystem for structuring and managing high-scale systems. By the end of the book, you will feel comfortable with designing safe, consistent, parallel, and high-performance applications in Rust.

Hands-On Convolutional Neural Networks with TensorFlow. Solve computer vision problems with modeling in TensorFlow and Python

Iffat Zafar, Giounona Tzanidou, Richard Burton, Nimesh Patel, ...

Convolutional Neural Networks (CNN) are one of the most popular architectures used in computer vision apps. This book is an introduction to CNNs through solving real-world problems in deep learning while teaching you their implementation in popular Python library - TensorFlow. By the end of the book, you will be training CNNs in no time!We start with an overview of popular machine learning and deep learning models, and then get you set up with a TensorFlow development environment. This environment is the basis for implementing and training deep learning models in later chapters. Then, you will use Convolutional Neural Networks to work on problems such as image classification, object detection, and semantic segmentation.After that, you will use transfer learning to see how these models can solve other deep learning problems. You will also get a taste of implementing generative models such as autoencoders and generative adversarial networks.Later on, you will see useful tips on machine learning best practices and troubleshooting. Finally, you will learn how to apply your models on large datasets of millions of images.

Hands-On Data Analysis with Pandas. Efficiently perform data collection, wrangling, analysis, and visualization using Python

Stefanie Molin

Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value.Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will be able to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding chapters, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data.By the end of this book, you will be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets.

Hands-On Data Preprocessing in Python. Learn how to effectively prepare data for successful data analytics

Roy Jafari

Hands-On Data Preprocessing is a primer on the best data cleaning and preprocessing techniques, written by an expert who’s developed college-level courses on data preprocessing and related subjects. With this book, you’ll be equipped with the optimum data preprocessing techniques from multiple perspectives, ensuring that you get the best possible insights from your data. You'll learn about different technical and analytical aspects of data preprocessing – data collection, data cleaning, data integration, data reduction, and data transformation – and get to grips with implementing them using the open source Python programming environment. The hands-on examples and easy-to-follow chapters will help you gain a comprehensive articulation of data preprocessing, its whys and hows, and identify opportunities where data analytics could lead to more effective decision making. As you progress through the chapters, you’ll also understand the role of data management systems and technologies for effective analytics and how to use APIs to pull data.By the end of this Python data preprocessing book, you'll be able to use Python to read, manipulate, and analyze data; perform data cleaning, integration, reduction, and transformation techniques, and handle outliers or missing values to effectively prepare data for analytic tools.

Hands-On Data Science for Marketing. Improve your marketing strategies with machine learning using Python and R

Yoon Hyup Hwang

Regardless of company size, the adoption of data science and machine learning for marketing has been rising in the industry. With this book, you will learn to implement data science techniques to understand the drivers behind the successes and failures of marketing campaigns. This book is a comprehensive guide to help you understand and predict customer behaviors and create more effectively targeted and personalized marketing strategies.This is a practical guide to performing simple-to-advanced tasks, to extract hidden insights from the data and use them to make smart business decisions. You will understand what drives sales and increases customer engagements for your products. You will learn to implement machine learning to forecast which customers are more likely to engage with the products and have high lifetime value. This book will also show you how to use machine learning techniques to understand different customer segments and recommend the right products for each customer. Apart from learning to gain insights into consumer behavior using exploratory analysis, you will also learn the concept of A/B testing and implement it using Python and R.By the end of this book, you will be experienced enough with various data science and machine learning techniques to run and manage successful marketing campaigns for your business.