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Learning Http 2


Learning Http 2
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Learning Http 2


Learning Http 2
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Author : Stephen Ludin
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2017-05-15

Learning Http 2 written by Stephen Ludin and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-15 with Computers categories.


Chapter 8. Debugging h2; Web Browser Developer Tools; Chrome Developer Tools; Firefox Developer Tools; Debugging h2 on iOS Using Charles Proxy; Debugging h2 on Android; WebPagetest; OpenSSL; OpenSSL Commands; nghttp2; Using nghttp; curl; Using curl; h2i; Wireshark; Summary; Chapter 9. What Is Next?; TCP or UDP?; QUIC; TLS 1.3; HTTP/3?; Summary; Appendix A. HTTP/2 Frames; The Frame Header; DATA; DATA Frame Fields; DATA Frame Flags; HEADERS; HEADERS Frame Fields; HEADERS Frame Flags; PRIORITY; PRIORITY Frame Fields; RST_STREAM; SETTINGS; SETTINGS Parameters; PUSH_PROMISE.



Learning Http 2


Learning Http 2
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Author : Stephen Ludin
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2017-07-17

Learning Http 2 written by Stephen Ludin and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-17 with categories.


HTTP is the foundational protocol for exchanging information across the World Wide Web. With HTTP, you'll learn all about something you use on a daily basis, perhaps without realizing what goes on behind the scenes. You'll quickly learn about resources, requests and responses, safe and unsafe methods, connections, cookies, security, and so much more. Equipped with the information in this book, you'll be able to write better web apps and services, and debug them when something goes wrong. This updated and expanded second edition of Book provides a user-friendly introduction to the subject, Taking a clear structural framework, it guides the reader through the subject's core elements. A flowing writing style combines with the use of illustrations and diagrams throughout the text to ensure the reader understands even the most complex of concepts. This succinct and enlightening overview is a required reading for all those interested in the subject . We hope you find this book useful in shaping your future career & Business.



Http 2 In Action


Http 2 In Action
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Author : Barry Pollard
language : en
Publisher: Simon and Schuster
Release Date : 2019-03-06

Http 2 In Action written by Barry Pollard and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-06 with Computers categories.


Summary HTTP/2 in Action is a complete guide to HTTP/2, one of the core protocols of the web. Because HTTP/2 has been designed to be easy to transition to, including keeping it backwards compatible, adoption is rapid and expected to increase over the next few years. Concentrating on practical matters, this interesting book presents key HTTP/2 concepts such as frames, streams, and multiplexing and explores how they affect the performance and behavior of your websites. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology HTTP—Hypertext Transfer Protocol—is the standard for exchanging messages between websites and browsers. And after 20 years, it's gotten a much-needed upgrade. With support for streams, server push, header compression, and prioritization, HTTP/2 delivers vast improvements in speed, security, and efficiency. About the Book HTTP/2 in Action teaches you everything you need to know to use HTTP/2 effectively. You'll learn how to optimize web performance with new features like frames, multiplexing, and push. You'll also explore real-world examples on advanced topics like flow control and dependencies. With ready-to-implement tips and best practices, this practical guide is sure to get you—and your websites—up to speed! What's Inside HTTP/2 for web developers Upgrading and troubleshooting Real-world examples and case studies QUIC and HTTP/3 About the Reader Written for web developers and site administrators. About the Authors Barry Pollard is a professional developer with two decades of experience developing, supporting, and tuning software and infrastructure. Table of Contents PART 1 MOVING TO HTTP/2 Web technologies and HTTP The road to HTTP/2 Upgrading to HTTP/2 PART 2 USING HTTP/2 HTTP/2 protocol basics Implementing HTTP/2 push Optimizing for HTTP/2 PART 3 ADVANCED HTTP/2 Advanced HTTP/2 concepts HPACK header compression PART 4 THE FUTURE OF HTTP TCP, QUIC, and HTTP/3 Where HTTP goes from here



Http The Definitive Guide


Http The Definitive Guide
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Author : David Gourley
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2002-09-27

Http The Definitive Guide written by David Gourley and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-09-27 with Computers categories.


This guide gives a complete and detailed description of the HTTP protocol and how it shapes the landscape of the Web by the technologies that it supports.



Deep Learning


Deep Learning
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Author : Ian Goodfellow
language : en
Publisher: MIT Press
Release Date : 2016-11-10

Deep Learning written by Ian Goodfellow and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-10 with Computers categories.


An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.



R For Data Science


R For Data Science
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Author : Hadley Wickham
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2016-12-12

R For Data Science written by Hadley Wickham and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-12 with Computers categories.


Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results



Reinforcement Learning


Reinforcement Learning
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Author : Richard S. Sutton
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Reinforcement Learning written by Richard S. Sutton and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.


Reinforcement learning is the learning of a mapping from situations to actions so as to maximize a scalar reward or reinforcement signal. The learner is not told which action to take, as in most forms of machine learning, but instead must discover which actions yield the highest reward by trying them. In the most interesting and challenging cases, actions may affect not only the immediate reward, but also the next situation, and through that all subsequent rewards. These two characteristics -- trial-and-error search and delayed reward -- are the most important distinguishing features of reinforcement learning. Reinforcement learning is both a new and a very old topic in AI. The term appears to have been coined by Minsk (1961), and independently in control theory by Walz and Fu (1965). The earliest machine learning research now viewed as directly relevant was Samuel's (1959) checker player, which used temporal-difference learning to manage delayed reward much as it is used today. Of course learning and reinforcement have been studied in psychology for almost a century, and that work has had a very strong impact on the AI/engineering work. One could in fact consider all of reinforcement learning to be simply the reverse engineering of certain psychological learning processes (e.g. operant conditioning and secondary reinforcement). Reinforcement Learning is an edited volume of original research, comprising seven invited contributions by leading researchers.



An Introduction To Statistical Learning


An Introduction To Statistical Learning
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Author : Gareth James
language : en
Publisher: Springer Nature
Release Date : 2023-06-30

An Introduction To Statistical Learning written by Gareth James and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-30 with Mathematics categories.


An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.



Interpretable Machine Learning


Interpretable Machine Learning
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Author : Christoph Molnar
language : en
Publisher: Lulu.com
Release Date : 2020

Interpretable Machine Learning written by Christoph Molnar and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Computers categories.


This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.



High Performance Browser Networking


High Performance Browser Networking
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Author : Ilya Grigorik
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2013-09-11

High Performance Browser Networking written by Ilya Grigorik and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-09-11 with Computers categories.


How prepared are you to build fast and efficient web applications? This eloquent book provides what every web developer should know about the network, from fundamental limitations that affect performance to major innovations for building even more powerful browser applicationsâ??including HTTP 2.0 and XHR improvements, Server-Sent Events (SSE), WebSocket, and WebRTC. Author Ilya Grigorik, a web performance engineer at Google, demonstrates performance optimization best practices for TCP, UDP, and TLS protocols, and explains unique wireless and mobile network optimization requirements. Youâ??ll then dive into performance characteristics of technologies such as HTTP 2.0, client-side network scripting with XHR, real-time streaming with SSE and WebSocket, and P2P communication with WebRTC. Deliver superlative TCP, UDP, and TLS performance Speed up network performance over 3G/4G mobile networks Develop fast and energy-efficient mobile applications Address bottlenecks in HTTP 1.x and other browser protocols Plan for and deliver the best HTTP 2.0 performance Enable efficient real-time streaming in the browser Create efficient peer-to-peer videoconferencing and low-latency applications with real-time WebRTC transports