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See below for a selection of the latest books from Internet browsers category. Presented with a red border are the Internet browsers books that have been lovingly read and reviewed by the experts at Lovereading. With expert reading recommendations made by people with a passion for books and some unique features Lovereading will help you find great Internet browsers books and those from many more genres to read that will keep you inspired and entertained. And it's all free!
Diversity in user queries makes it challenging for search engines to effectively return a set of relevant results. Both user intentions to search the web and types of queries are vastly varied; consequently, horizontal and vertical search engines are developed to answer user queries more efficiently. However, these search engines present a variety of problems in web searching. Result Page Generation for Web Searching: Emerging Research and Opportunities is an essential reference publication that focuses on taking advantages from text and web mining in order to address the issues of recommendation and visualization in web searching. Highlighting a wide range of topics such as navigational searching, resource identification, and ambiguous queries, this book is ideally designed for computer engineers, web designers, programmers, academicians, researchers, and students.
Use the power of deep learning with Python to build and deploy intelligent web applications Key Features Create next-generation intelligent web applications using Python libraries such as Flask and Django Implement deep learning algorithms and techniques for performing smart web automation Integrate neural network architectures to create powerful full-stack web applications Book DescriptionWhen used effectively, deep learning techniques can help you develop intelligent web apps. In this book, you'll cover the latest tools and technological practices that are being used to implement deep learning in web development using Python. Starting with the fundamentals of machine learning, you'll focus on DL and the basics of neural networks, including common variants such as convolutional neural networks (CNNs). You'll learn how to integrate them into websites with the frontends of different standard web tech stacks. The book then helps you gain practical experience of developing a deep learning-enabled web app using Python libraries such as Django and Flask by creating RESTful APIs for custom models. Later, you'll explore how to set up a cloud environment for deep learning-based web deployments on Google Cloud and Amazon Web Services (AWS). Next, you'll learn how to use Microsoft's intelligent Emotion API, which can detect a person's emotions through a picture of their face. You'll also get to grips with deploying real-world websites, in addition to learning how to secure websites using reCAPTCHA and Cloudflare. Finally, you'll use NLP to integrate a voice UX through Dialogflow on your web pages. By the end of this book, you'll have learned how to deploy intelligent web apps and websites with the help of effective tools and practices. What you will learn Explore deep learning models and implement them in your browser Design a smart web-based client using Django and Flask Work with different Python-based APIs for performing deep learning tasks Implement popular neural network models with TensorFlow.js Design and build deep web services on the cloud using deep learning Get familiar with the standard workflow of taking deep learning models into production Who this book is forThis deep learning book is for data scientists, machine learning practitioners, and deep learning engineers who are looking to perform deep learning techniques and methodologies on the web. You will also find this book useful if you're a web developer who wants to implement smart techniques in the browser to make it more interactive. Working knowledge of the Python programming language and basic machine learning techniques will be beneficial.
Until recently, learning CoreDNS required reading the code or combing through the skimpy documentation on the website. No longer. With this practical book, developers and operators working with Docker or Linux containers will learn how to use this standard DNS server with Kubernetes. John Belamaric, senior staff software engineer at Google, and Cricket Liu, chief DNS architect at Infoblox, show you how to configure CoreDNS using real-world configuration examples to achieve specific purposes. You'll learn the basics of DNS, including how it functions as a location broker in container environments and how it ties into Kubernetes. Dive into DNS theory: the DNS namespace, domain names, domains, and zones Learn how to configure your CoreDNS server Manage and serve basic and advanced zone data with CoreDNS Configure CoreDNS service discovery with etcd and Kubernetes Learn one of the most common use cases for CoreDNS: the integration with Kubernetes Manipulate queries and responses as they flow through the plug-in chain Monitor and troubleshoot the availability and performance of your DNS service Build custom versions of CoreDNS and write your own plug-ins
Master the intricacies of Elasticsearch 7.0 and use it to create flexible and scalable search solutions Key Features Master the latest distributed search and analytics capabilities of Elasticsearch 7.0 Perform searching, indexing, and aggregation of your data at scale Discover tips and techniques for speeding up your search query performance Book DescriptionBuilding enterprise-grade distributed applications and executing systematic search operations call for a strong understanding of Elasticsearch and expertise in using its core APIs and latest features. This book will help you master the advanced functionalities of Elasticsearch and understand how you can develop a sophisticated, real-time search engine confidently. In addition to this, you'll also learn to run machine learning jobs in Elasticsearch to speed up routine tasks. You'll get started by learning to use Elasticsearch features on Hadoop and Spark and make search results faster, thereby improving the speed of query results and enhancing the customer experience. You'll then get up to speed with performing analytics by building a metrics pipeline, defining queries, and using Kibana for intuitive visualizations that help provide decision-makers with better insights. The book will later guide you through using Logstash with examples to collect, parse, and enrich logs before indexing them in Elasticsearch. By the end of this book, you will have comprehensive knowledge of advanced topics such as Apache Spark support, machine learning using Elasticsearch and scikit-learn, and real-time analytics, along with the expertise you need to increase business productivity, perform analytics, and get the very best out of Elasticsearch. What you will learn Pre-process documents before indexing in ingest pipelines Learn how to model your data in the real world Get to grips with using Elasticsearch for exploratory data analysis Understand how to build analytics and RESTful services Use Kibana, Logstash, and Beats for dashboard applications Get up to speed with Spark and Elasticsearch for real-time analytics Explore the basics of Spring Data Elasticsearch, and understand how to index, search, and query in a Spring application Who this book is forThis book is for Elasticsearch developers and data engineers who want to take their basic knowledge of Elasticsearch to the next level and use it to build enterprise-grade distributed search applications. Prior experience of working with Elasticsearch will be useful to get the most out of this book.
DESCRIPTION Modern applications are constantly sending, receiving, and reacting to streams of data including internal messages, user and system events, and sensor input. Reactive Extensions (Rx) is a .NET library that abstracts away the sources of events and provides tools to effectively manage concerns like concurrency, scalability, error handling, and performance. Rx includes more than 600 operators with variants that can composed together to build reactive client and server-side applications that handle events asynchronously in a way that maximizes responsiveness, resiliency, and elasticity. Reactive Extensions in .NET is a step-by-step guide that shows developershow to build event-driven applications using the Rx library. First, it provides an overview of the design and architecture of Rx-based reactive applications. Then, it looks at the rich query capabilities that Rx provides and the Rx concurrency model that allows developers to control asynchronicity of code and processing of event handlers. The book also discusses consuming event streams, using schedulers to manage time, and working with Rx operators to filter, transform, and group events. Readers new to Rx will be able to learn from the ground up and those using Rx will get a deeper look at how to leverage Rx in existing reactive applications. KEY FEATURES* Step-by-step guide * Real life examples using Rx * Great for readers both new to Rx and those already using RxAUDIENCE Readers should understand OOP concepts and be comfortable coding in C#. ABOUT THE TECHNOLOGY Reactive Extensions (Rx) is a .NET library that abstracts away the sources of events and provides tools to effectively manage concerns like concurrency, scalability, error handling, and performance. Rx includes more than 600 operators with variants that can composed together to build reactive client and server-side applications that handle events asynchronously in a way that maximizes responsiveness, resiliency, and elasticity.