Hands-On Reactive Programming with Python by Romain Picard

Hands-On Reactive Programming with Python by Romain Picard
Requirements: .PDF reader, 44,2 MB
Overview: Reactive programming is central to many concurrent systems, but it’s famous for its steep learning curve, which makes most developers feel like they’re hitting a wall. With this book, you will get to grips with reactive programming by steadily exploring various concepts. This hands-on guide gets you started with Reactive Programming (RP) in Python. You will learn abouta the principles and benefits of using RP, which can be leveraged to build powerful concurrent applications. As you progress through the chapters, you will be introduced to the paradigm of Functional and Reactive Programming (FaRP), observables and observers, and concurrency and parallelism. The book will then take you through the implementation of an audio transcoding server and introduce you to a library that helps in the writing of FaRP code. You will understand how to use third-party services and dynamically reconfigure an application. By the end of the book, you will also have learned how to deploy and scale your applications with Docker and Traefik and explore the significant potential behind the reactive streams concept, and you’ll have got to grips with a comprehensive set of best practices.
Genre: Non-Fiction > Tech & Devices

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Rapid Java Persistence and Microservices

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Rapid Java Persistence and Microservices: Persistence Made Easy Using Java EE8, JPA and Spring

Gain all the essentials you need to create scalable microservices, which will help you solve real challenges when deploying services into production. This book will take you through creating a scalable data layer with polygot persistence. You’ll cover data access and query patterns in Spring and JPA in high-performance environments. As part of this topic, you’ll see the advantages of multiple persistence frameworks in Java and especially the easy persistence offered by NoSQL databases and reactive web solutions.

What You Will Learn

The last few chapters of Rapid Java Persistence and Microservices present advanced concepts that are useful for very high-performance real-time applications: you’ll implement applications using Spring’s good support for Web sockets in their raw form as well as for connecting to message brokers such as RabbitMQ. This can be useful for applications such as navigation systems and gaming platforms.

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Python Deep Learning – Second Edition

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Python Deep Learning, 2nd Edition: Learn advanced state-of-the-art deep learning techniques and their applications using popular Python libraries

With the surge in artificial intelligence in applications catering to both business and consumer needs, deep learning is more important than ever for meeting current and future market demands. With this book, you’ll explore deep learning, and learn how to put machine learning to use in your projects.

This book will get you up to speed with deep learning, deep neural networks, and how to train them with high-performance algorithms and popular Python frameworks. You’ll uncover different neural network architectures, such as convolutional networks, recurrent neural networks, long short-term memory (LSTM) networks, and capsule networks. You’ll also learn how to solve problems in the fields of computer vision, natural language processing (NLP), and speech recognition. You’ll study generative model approaches such as variational autoencoders and Generative Adversarial Networks (GANs) to generate images. As you delve into newly evolved areas of reinforcement learning, you’ll gain an understanding of state-of-the-art algorithms that are the main components behind popular games Go, Atari, and Dota.

By the end of the book, you will be well-versed with the theory of deep learning along with its real-world applications.

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Pro iPhone Development with Swift 5

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Pro iPhone Development with Swift 5: Design and Manage Top Quality Apps

If you’ve already learned the basics of Swift and iOS programming, it’s time to take your skills to the next level. In this follow up work to the best-selling Beginning iPhone Development with Swift 5, you’ll learn tips for organizing and debugging Swift code, using multi-threaded programming with Grand Central Dispatch, passing data between view controllers, and designing apps for multiple languages.

You’ll also see how to play audio and video files, access the camera and save pictures to the Photos library, use location services to pinpoint your position on a map, display web pages, and create animation to spice up any user interface. Finally, you’ll learn how to use Apple’s advanced frameworks for machine learning, facial and text recognition, and creating augmented reality apps.

What you will learn

Pro iPhone Development with Swift 5 provides insightful instruction on how to improve your existing apps or create powerful new iOS apps using the latest version of the Swift programming language.

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Modern C++: Efficient and Scalable Application Development

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Modern C++: Efficient and Scalable Application Development: Create apps in C++ and leverage its latest features using modern programming techniques

C++ is one of the most widely used programming languages. It is fast, flexible, and used to solve many programming problems.

This Learning Path gives you an in-depth and hands-on experience of working with C++, using the latest recipes and understanding most recent developments. You will explore C++ programming constructs by learning about language structures, functions, and classes, which will help you identify the execution flow through code. You will also understand the importance of the C++ standard library as well as memory allocation for writing better and faster programs.

Modern C++: Efficient and Scalable Application Development deals with the challenges faced with advanced C++ programming. You will work through advanced topics such as multithreading, networking, concurrency, lambda expressions, and many more recipes.

By the end of this Learning Path Modern C++: Efficient and Scalable Application Development, you will have all the skills to become a master C++ programmer.

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Machine Learning in Java – Second Edition

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Machine Learning in Java, 2nd Edition: Leverage the power of Java and its associated machine learning libraries to build powerful predictive models

As the amount of data in the world continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognition. This makes machine learning well-suited to the present-day era of big data and Data Science. The main challenge is how to transform data into actionable knowledge.

Machine Learning in Java will provide you with the techniques and tools you need. You will start by learning how to apply machine learning methods to a variety of common tasks including classification, prediction, forecasting, market basket analysis, and clustering. The code in this book works for JDK 8 and above, the code is tested on JDK 11.

Moving on, you will discover how to detect anomalies and fraud, and ways to perform activity recognition, image recognition, and text analysis. By the end of the Machine Learning in Java, Second Edition book, you will have explored related web resources and technologies that will help you take your learning to the next level.

By applying the most effective machine learning methods to real-world problems, you will gain hands-on experience that will transform the way you think about data.

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Hands-On Meta Learning with Python

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Hands-On Meta Learning with Python: Explore a diverse set of meta-learning algorithms and techniques to enable human-like cognition for your machine learning models using various Python frameworks

Meta learning is an exciting research trend in machine learning, which enables a model to understand the learning process. Unlike other ML paradigms, with meta learning you can learn from small datasets faster.

Hands-On Meta Learning with Python starts by explaining the fundamentals of meta learning and helps you understand the concept of learning to learn. You will delve into various one-shot learning algorithms, like siamese, prototypical, relation and memory-augmented networks by implementing them in TensorFlow and Keras. As you make your way through the book, you will dive into state-of-the-art meta learning algorithms such as MAML, Reptile, and CAML. You will then explore how to learn quickly with Meta-SGD and discover how you can perform unsupervised learning using meta learning with CACTUs. In the concluding chapters, you will work through recent trends in meta learning such as adversarial meta learning, task agnostic meta learning, and meta imitation learning.

By the end of this Hands-On Meta Learning with Python book, you will be familiar with state-of-the-art meta learning algorithms and able to enable human-like cognition for your machine learning models.

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Go Machine Learning Projects

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Go Machine Learning Projects: Work through exciting projects to explore the capabilities of Go and Machine Learning

Go is the perfect language for machine learning; it helps to clearly describe complex algorithms, and also helps developers to understand how to run efficient optimized code. This book will teach you how to implement machine learning in Go to make programs that are easy to deploy and code that is not only easy to understand and debug, but also to have its performance measured.

The book begins by guiding you through setting up your machine learning environment with Go libraries and capabilities. You will then plunge into regression analysis of a real-life house pricing dataset and build a classification model in Go to classify emails as spam or ham. Using Gonum, Gorgonia, and STL, you will explore time series analysis along with decomposition and clean up your personal Twitter timeline by clustering tweets. In addition to this, you will learn how to recognize handwriting using neural networks and convolutional neural networks. Lastly, you’ll learn how to choose the most appropriate machine learning algorithms to use for your projects with the help of a facial detection project.

By the end of this Go Machine Learning Projects book, you will have developed a solid machine learning mindset, a strong hold on the powerful Go toolkit, and a sound understanding of the practical implementations of machine learning algorithms in real-world projects.

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Foundations of Libvirt Development

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Foundations of Libvirt Development: How to Set Up and Maintain a Virtual Machine Environment with Python

Discover the essential concepts of libvirt development and see how to interface to Linux virtualization environments, such as QEMU/KVM, XEN, Virtuozzo, VMWare ESX, LXC, Bhyve, and more. This book will prepare you to set up and maintain a virtual machine environment.

You’ll start by reviewing virtualization in general and then move on to libvirt-specific concepts using Python, including virtualized operating systems and networks, connections, storage pools, and event and error handling. This work concludes with a comprehensive look at the XML schema definitions for domains, networks, devices, network filtering, storage, node devices, and more.

What You’ll Learn

The libvirt API covers the entire life cycle of virtual objects, from creation to destruction. It contains everything needed for the management of a virtual object during that life cycle. While libvirt has APIs that support many languages, Foundations of Libvirt Development concentrates on Python exclusively, and how to use the APIs to control virtual machines under the QEMU/KVM system. and more.

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Foundations of Libvirt Development

eBook Details:

eBook Description:

Foundations of Libvirt Development: How to Set Up and Maintain a Virtual Machine Environment with Python

Discover the essential concepts of libvirt development and see how to interface to Linux virtualization environments, such as QEMU/KVM, XEN, Virtuozzo, VMWare ESX, LXC, Bhyve, and more. This book will prepare you to set up and maintain a virtual machine environment.

You’ll start by reviewing virtualization in general and then move on to libvirt-specific concepts using Python, including virtualized operating systems and networks, connections, storage pools, and event and error handling. This work concludes with a comprehensive look at the XML schema definitions for domains, networks, devices, network filtering, storage, node devices, and more.

What You’ll Learn

The libvirt API covers the entire life cycle of virtual objects, from creation to destruction. It contains everything needed for the management of a virtual object during that life cycle. While libvirt has APIs that support many languages, Foundations of Libvirt Development concentrates on Python exclusively, and how to use the APIs to control virtual machines under the QEMU/KVM system. and more.

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Rust Quick Start Guide

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Rust Quick Start Guide: Get familiar with writing programs in the trending new systems programming language that brings together the powerful performance of low-level languages with the advanced features like thread safety in multi-threaded code

Rust is an emerging programming language applicable to areas such as embedded programming, network programming, system programming, and web development. This book will take you from the basics of Rust to a point where your code compiles and does what you intend it to do!

This Rust Quick Start Guide book starts with an introduction to Rust and how to get set for programming, including the rustup and cargo tools for managing a Rust installation and development workflow.

Then you’ll learn about the fundamentals of structuring a Rust program, such as functions, mutability, data structures, implementing behavior for types, and many more. You will also learn about concepts that Rust handles differently from most other languages.

After understanding the Basics of Rust programming, you will learn about the core ideas, such as variable ownership, scope, lifetime, and borrowing. After these key ideas, you will explore making decisions in Rust based on data types by learning about match and if let expressions. After that, you’ll work with different data types in Rust, and learn about memory management and smart pointers.

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Node.js: The Collection

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Node.js: The Collection

While there have been quite a few attempts to get JavaScript working as a server-side language, Node.js (frequently just called Node) has been the first environment that’s gained any traction. It’s now used by companies such as Netflix, Uber and Paypal to power their web apps. Node allows for blazingly fast performance; thanks to its event loop model, common tasks like network connection and database I/O can be executed very quickly indeed.

Node.js: The Collection contains three books that will help get you up and running with Node. It contains:

From a beginner’s point of view, one of Node’s obvious advantages is that it uses JavaScript, a ubiquitous language that many developers are comfortable with. If you can write JavaScript for the client-side, writing server-side applications with Node should not be too much of a stretch for you.

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Learn Vue.js: The Collection

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Learn Vue.js: The Collection

Learn Vue.js: The Collection is a collection of three books covering crucial Vue topics. It contains:

Since its release in 2014, Vue.js has seen a meteoric rise to popularity and is is now considered one of the primary front-end frameworks, and not without good reason. Its component-based architecture was designed to be flexible and easy to adopt, making it just as easy to integrate into projects and use alongside non-Vue code as it is to build complex client-side applications.

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Haskell Quick Syntax Reference

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Haskell Quick Syntax Reference: A Pocket Guide to the Language, APIs, and Library

This condensed code and syntax reference presents the essential Haskell syntax in a well-organized format that can be used as a quick and handy reference, including applications to cloud computing and data analysis. This book covers the functional programming features of Haskell as well as strong static typing, lazy evaluation, extensive parallelism, and concurrency.

What You Will Learn

You won’t find any technical jargon, bloated samples, drawn out history lessons, or witty stories in this book. What you will find is a language reference that is concise, to the point and highly accessible. The book is packed with useful information and is a must-have for any Haskell programmer working in big data, data science, and cloud computing.

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