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Learning Go With Networking


Learning Go With Networking
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Network Programming With Go


Network Programming With Go
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Author : Adam Woodbeck
language : en
Publisher: No Starch Press
Release Date : 2021-03-30

Network Programming With Go written by Adam Woodbeck and has been published by No Starch Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-30 with Computers categories.


Network Programming with Go teaches you how to write clean, secure network software with the programming language designed to make it seem easy. Build simple, reliable, network software Combining the best parts of many other programming languages, Go is fast, scalable, and designed for high-performance networking and multiprocessing. In other words, it’s perfect for network programming. Network Programming with Go will help you leverage Go to write secure, readable, production-ready network code. In the early chapters, you’ll learn the basics of networking and traffic routing. Then you’ll put that knowledge to use as the book guides you through writing programs that communicate using TCP, UDP, and Unix sockets to ensure reliable data transmission. As you progress, you’ll explore higher-level network protocols like HTTP and HTTP/2 and build applications that securely interact with servers, clients, and APIs over a network using TLS. You'll also learn: Internet Protocol basics, such as the structure of IPv4 and IPv6, multicasting, DNS, and network address translation Methods of ensuring reliability in socket-level communications Ways to use handlers, middleware, and multiplexers to build capable HTTP applications with minimal code Tools for incorporating authentication and encryption into your applications using TLS Methods to serialize data for storage or transmission in Go-friendly formats like JSON, Gob, XML, and protocol buffers Ways of instrumenting your code to provide metrics about requests, errors, and more Approaches for setting up your application to run in the cloud (and reasons why you might want to) Network Programming with Go is all you’ll need to take advantage of Go’s built-in concurrency, rapid compiling, and rich standard library. Covers Go 1.15 (Backward compatible with Go 1.12 and higher)



Network Programming With Go


Network Programming With Go
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Author : Jan Newmarch
language : en
Publisher: Apress
Release Date : 2017-05-15

Network Programming With Go written by Jan Newmarch and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-15 with Computers categories.


Dive into key topics in network architecture and Go, such as data serialization, application level protocols, character sets and encodings. This book covers network architecture and gives an overview of the Go language as a primer, covering the latest Go release. Beyond the fundamentals, Network Programming with Go covers key networking and security issues such as HTTP and HTTPS, templates, remote procedure call (RPC), web sockets including HTML5 web sockets, and more. Additionally, author Jan Newmarch guides you in building and connecting to a complete web server based on Go. This book can serve as both as an essential learning guide and reference on Go networking. What You Will Learn Master network programming with Go Carry out data serialization Use application-level protocols Manage character sets andencodings Deal with HTTP(S) Build a complete Go-based web server Work with RPC, web sockets, and more Who This Book Is For Experienced Go programmers and other programmers with some experience with the Go language.



Learning Go With Networking


Learning Go With Networking
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Author : Yogananth T. V.
language : en
Publisher: BPB Publications
Release Date : 2025-05-29

Learning Go With Networking written by Yogananth T. V. and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-29 with Computers categories.


DESCRIPTION Golang has emerged as a powerful language for networking, known for its efficiency and concurrency, making it ideal for building resilient and scalable network applications. This book is designed to equip networking professionals with the Golang skills needed to navigate this dynamic landscape, providing a practical guide from fundamental concepts to advanced network programming. This book systematically guides you through Golang's core features, including concurrency, generics, and error handling, before diving into essential networking principles like IP, TCP, and UDP. You will learn to develop applications, design synchronous and asynchronous APIs (with a focus on Ponzu and Keycloak), and effectively handle data using formats like JSON and XML, along with stream processing with AMQP, Kafka, and MQTT. The book explores Golang network packages for protocols such as ARP, FTP, DNS, and raw sockets. It also emphasizes performance optimization, covering I/O, caching, and database techniques, and automation strategies, including device, network, and cloud deployment, along with Cisco DevNet. Security is thoroughly addressed, covering authentication, cryptography (SSL/TLS, asymmetric/symmetric), certificate handling, and OWASP Top 10 vulnerabilities, and the book concludes with an exploration of network penetration testing techniques. By the end of this book, readers will gain a solid foundation in Golang and its application to networking, enabling them to build efficient, secure, and automated network solutions and understand the security landscape, from defensive best practices to offensive techniques. WHAT YOU WILL LEARN ● Build scalable backend services using Go and its libraries. ● Understand TCP/UDP networking through real Go-based examples. ● Develop secure APIs with authentication and token handling. ● Automate infrastructure tasks using Golang and DevNet. ● Identify and fix OWASP Top 10 vulnerabilities in Go. ● Perform ethical hacking in a controlled lab environment. ● Optimize Go applications using profiling and performance tools. ● Handle data formats like JSON, XML, and Base64 effectively. WHO THIS BOOK IS FOR This book is for software developers, DevOps engineers, backend architects, and cybersecurity professionals who want to build scalable, secure, and efficient systems using Golang. It is ideal for anyone working in infrastructure, automation, or cloud-native development looking to sharpen their development skills in Golang with respect to network programming. TABLE OF CONTENTS 1. Introduction to Go Language 2. Networking Essentials 3. Application Essentials 4. Data Essentials 5. Network Packages Unleased 6. Introduction to Performance Essentials 7. Automation Essentials 8. Authentication, Authorization, and Cryptography 9. OWASP with Golang 10. Hacking the Network APPENDIX: Technical Essentials



Go Programming For Network Operations A Golang Network Automation Handbook


Go Programming For Network Operations A Golang Network Automation Handbook
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Author : Tom McAllen
language : en
Publisher: Independently Published
Release Date : 2019-02-08

Go Programming For Network Operations A Golang Network Automation Handbook written by Tom McAllen and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-08 with Computers categories.


This book illustrates how to apply Go programming to network operations. The topics cover common use cases through examples that are designed to act as a guide and serve as a reference. The reader is assumed to have already gained a fundamental understanding of Go programming; however, the examples are explained for additional clarification. The focus is on using Go for network operations, not on the language itself.



Security With Go


Security With Go
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Author : John Daniel Leon
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-01-31

Security With Go written by John Daniel Leon and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-31 with Computers categories.


The first stop for your security needs when using Go, covering host, network, and cloud security for ethical hackers and defense against intrusion Key Features First introduction to Security with Golang Adopting a Blue Team/Red Team approach Take advantage of speed and inherent safety of Golang Works as an introduction to security for Golang developers Works as a guide to Golang security packages for recent Golang beginners Book Description Go is becoming more and more popular as a language for security experts. Its wide use in server and cloud environments, its speed and ease of use, and its evident capabilities for data analysis, have made it a prime choice for developers who need to think about security. Security with Go is the first Golang security book, and it is useful for both blue team and red team applications. With this book, you will learn how to write secure software, monitor your systems, secure your data, attack systems, and extract information. Defensive topics include cryptography, forensics, packet capturing, and building secure web applications. Offensive topics include brute force, port scanning, packet injection, web scraping, social engineering, and post exploitation techniques. What you will learn Learn the basic concepts and principles of secure programming Write secure Golang programs and applications Understand classic patterns of attack Write Golang scripts to defend against network-level attacks Learn how to use Golang security packages Apply and explore cryptographic methods and packages Learn the art of defending against brute force attacks Secure web and cloud applications Who this book is for Security with Go is aimed at developers with basics in Go to the level that they can write their own scripts and small programs without difficulty. Readers should be familiar with security concepts, and familiarity with Python security applications and libraries is an advantage, but not a necessity.



Deep Learning For Coders With Fastai And Pytorch


Deep Learning For Coders With Fastai And Pytorch
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Author : Jeremy Howard
language : en
Publisher: O'Reilly Media
Release Date : 2020-06-29

Deep Learning For Coders With Fastai And Pytorch written by Jeremy Howard and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-29 with Computers categories.


Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala



The Go Programming Language


The Go Programming Language
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Author : Brian W. Kernighan
language : en
Publisher: Addison-Wesley Professional
Release Date : 2015-08-27

The Go Programming Language written by Brian W. Kernighan and has been published by Addison-Wesley Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-08-27 with Computers categories.


The Go Programming Language is the authoritative resource for any programmer who wants to learn Go. It shows how to write clear and idiomatic Go to solve real-world problems. The book does not assume prior knowledge of Go nor experience with any specific language, so you'll find it accessible whether you're most comfortable with JavaScript, Ruby, Python, Java, or C++. The first chapter is a tutorial on the basic concepts of Go, introduced through programs for file I/O and text processing, simple graphics, and web clients and servers. Early chapters cover the structural elements of Go programs: syntax, control flow, data types, and the organization of a program into packages, files, and functions. The examples illustrate many packages from the standard library and show how to create new ones of your own. Later chapters explain the package mechanism in more detail, and how to build, test, and maintain projects using the go tool. The chapters on methods and interfaces introduce Go's unconventional approach to object-oriented programming, in which methods can be declared on any type and interfaces are implicitly satisfied. They explain the key principles of encapsulation, composition, and substitutability using realistic examples. Two chapters on concurrency present in-depth approaches to this increasingly important topic. The first, which covers the basic mechanisms of goroutines and channels, illustrates the style known as communicating sequential processes for which Go is renowned. The second covers more traditional aspects of concurrency with shared variables. These chapters provide a solid foundation for programmers encountering concurrency for the first time. The final two chapters explore lower-level features of Go. One covers the art of metaprogramming using reflection. The other shows how to use the unsafe package to step outside the type system for special situations, and how to use the cgo tool to create Go bindings for C libraries. The book features hundreds of interesting and practical examples of well-written Go code that cover the whole language, its most important packages, and a wide range of applications. Each chapter has exercises to test your understanding and explore extensions and alternatives. Source code is freely available for download from http://gopl.io/ and may be conveniently fetched, built, and installed using the go get command.



Deep Learning And The Game Of Go


Deep Learning And The Game Of Go
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Author : Kevin Ferguson
language : en
Publisher: Simon and Schuster
Release Date : 2019-01-06

Deep Learning And The Game Of Go written by Kevin Ferguson 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 2019-01-06 with Computers categories.


Summary Deep Learning and the Game of Go teaches you how to apply the power of deep learning to complex reasoning tasks by building a Go-playing AI. After exposing you to the foundations of machine and deep learning, you'll use Python to build a bot and then teach it the rules of the game. Foreword by Thore Graepel, DeepMind Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology The ancient strategy game of Go is an incredible case study for AI. In 2016, a deep learning-based system shocked the Go world by defeating a world champion. Shortly after that, the upgraded AlphaGo Zero crushed the original bot by using deep reinforcement learning to master the game. Now, you can learn those same deep learning techniques by building your own Go bot! About the Book Deep Learning and the Game of Go introduces deep learning by teaching you to build a Go-winning bot. As you progress, you'll apply increasingly complex training techniques and strategies using the Python deep learning library Keras. You'll enjoy watching your bot master the game of Go, and along the way, you'll discover how to apply your new deep learning skills to a wide range of other scenarios! What's inside Build and teach a self-improving game AI Enhance classical game AI systems with deep learning Implement neural networks for deep learning About the Reader All you need are basic Python skills and high school-level math. No deep learning experience required. About the Author Max Pumperla and Kevin Ferguson are experienced deep learning specialists skilled in distributed systems and data science. Together, Max and Kevin built the open source bot BetaGo. Table of Contents PART 1 - FOUNDATIONS Toward deep learning: a machine-learning introduction Go as a machine-learning problem Implementing your first Go bot PART 2 - MACHINE LEARNING AND GAME AI Playing games with tree search Getting started with neural networks Designing a neural network for Go data Learning from data: a deep-learning bot Deploying bots in the wild Learning by practice: reinforcement learning Reinforcement learning with policy gradients Reinforcement learning with value methods Reinforcement learning with actor-critic methods PART 3 - GREATER THAN THE SUM OF ITS PARTS AlphaGo: Bringing it all together AlphaGo Zero: Integrating tree search with reinforcement learning



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.



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.