Blockchain concepts and the Hyperledger technologies are hot topics. Hyperledger is an open source project to create private blockchain applications for different domains including finance, banking, supply chain, IoT and much more. This book will be an easy reference to explore and build blockchain networks using Hyperledger services. This book will start with explaining the blockchain evolution and then proceed to an overview of technologies like Ethereum, R3 Corda, Coco, and Hyperledger. We will learn how to set up and launch Hyperledger Fabric in Bluemix. We will look into the architecture and the components of Hyperledger Fabric which are used to build private blockchain applications. Later we will delve into how we can interact with Hyperledger Fabric blockchain to build private networks from scratch covering all the required principles such as chaincode, smart contracts, cryptocurrencies and much more on the Hyperledger network. By the end of this book, you will be able to build and deploy your own decentralized applications using Hyperledger addressing key pain points encountered in blockchain lifecycle.

Hands-On Machine Learning with Scikit-Learn and TensorFlow 英文原版

英文电子书。。epub格式

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 2ed 2019.pdf Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow SECOND EDITION Concepts, Tools, and Techniques to Build Intelligent Systems

Qt 5是Qt的最新版本，使您能够为多个目标开发具有复杂用户界面的应用程序。它为您提供了更快，更智能的方法，可以为多个平台创建现代UI和应用程序。本书将教您设计和构建功能性，吸引力和用户友好的图形用户界面。 在本书的最初部分，您将了解Qt 5是什么以及您可以用它做什么。您将探索Qt Designer，发现Qt 5中通常使用的不同类型的小部件，然后将您的应用程序连接到数据库以执行动态操作。接下来，您将了解到Qt 5图表，它允许您轻松呈现不同类型的图形和图表，并在您的应用程序中合并列表视图窗口小部件。您还将在本书的过程中使用各种Qt模块，如QtLocation，QtWebEngine和网络模块。最后，我们将专注于使用QT 5进行跨平台开发，使您能够编写一次代码并在任何地方运行，包括移动平台。 在本书的最后，您将成功了解高端GUI应用程序，并将能够构建更多功能更强大的跨平台应用程序。

Hands-On Automated Machine Learning 英文无水印转化版pdf pdf所有页面使用FoxitReader、PDF-XChangeViewer、SumatraPDF和Firefox测试都可以打开 本资源转载自网络，如有侵权，请联系上传者或csdn删除 查看此书详细信息请在美国亚马逊官网搜索此书

Hands-On Intelligent Agents with OpenAI Gym_ Your guide to developing AI agents using deep reinforcement learning

Neural networks have made a surprise comeback in the last few years and have brought tremendous innovation in the world of artificial intelligence. The goal of this book is to provide C# programmers with practical guidance in solving complex computational challenges using neural networks and C# libraries such as CNTK, and TensorFlowSharp. This book will take you on a step-by-step practical journey, covering everything from the mathematical and theoretical aspects of neural networks, to building your own deep neural networks into your applications with the C# and .NET frameworks. This book begins by giving you a quick refresher of neural networks. You will learn how to build a neural network from scratch using packages such as Encog, Aforge, and Accord. You will learn about various concepts and techniques, such as deep networks, perceptrons, optimization algorithms, convolutional networks, and autoencoders. You will learn ways to add intelligent features to your .NET apps, such as facial and motion detection, object detection and labeling, language understanding, knowledge, and intelligent search. Throughout this book, you will be working on interesting demonstrations that will make it easier to implement complex neural networks in your enterprise applications.

Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started. * Explore the machine learning landscape, particularly neural nets * Use Scikit-Learn to track an example machine-learning project end-to-end * Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods * Use the TensorFlow library to build and train neural nets * Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning * Learn techniques for training and scaling deep neural nets

Get to grips with modern software demands by learning the effective uses of Rust's powerful memory safety. Key Features Learn and improve the sequential performance characteristics of your software Understand the use of operating system processes in a high-scale concurrent system Learn of the various coordination methods available in the Standard library Book Description 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. What you will learn Probe your programs for performance and accuracy issues Create your own threading and multi-processing environment in Rust Use coarse locks from Rust’s Standard library Solve common synchronization problems or avoid synchronization using atomic programming Build lock-free/wait-free structures in Rust and understand their implementat