Implementing Cisco Networking Solutions. Configure, implement, and manage complex network designs

Harpreet Singh

Most enterprises use Cisco networking equipment to design and implement their networks. However, some networks outperform networks in other enterprises in terms of performance and meeting new business demands, because they were designed with a visionary approach.The book starts by describing the various stages in the network lifecycle and covers the plan, build, and operate phases. It covers topics that will help network engineers capture requirements, choose the right technology, design and implement the network, and finally manage and operate the network. It divides the overall network into its constituents depending upon functionality, and describe the technologies used and the design considerations for each functional area. The areas covered include the campus wired network, wireless access network, WAN choices, datacenter technologies, and security technologies. It also discusses the need to identify business-critical applications on the network, and how to prioritize these applications by deploying QoS on the network.Each topic provides the technology choices, and the scenario, involved in choosing each technology, and provides configuration guidelines for configuring and implementing solutions in enterprise networks.

MQTT Essentials - A Lightweight IoT Protocol. Send and receive messages with the MQTT protocol for your IoT solutions

Gaston C. Hillar

This step-by-step guide will help you gain a deep understanding of the lightweight MQTT protocol. We’ll begin with the specific vocabulary of MQTT and its working modes, followed by installing a Mosquitto MQTT broker. Then, you will use best practices to secure the MQTT Mosquitto broker to ensure that only authorized clients are able to publish and receive messages. Once you have secured the broker with the appropriate configuration, you will develop a solution that controls a drone with Python.Further on, you will use Python on a Raspberry Pi 3 board to process commands and Python on Intel Boards (Joule, Edison and Galileo). You will then connect to the MQTT broker, subscribe to topics, send messages, and receive messages in Python. You will also develop a solution that interacts with sensors in Java by working with MQTT messages. Moving forward, you will work with an asynchronous API with callbacks to make the sensors interact with MQTT messages. Following the same process, you will develop an iOS app with Swift 3, build a website that uses WebSockets to connect to the MQTT broker, and control home automation devices with HTML5, JavaScript code, Node.js and MQTT messages

Hands-On Data Science with the Command Line. Automate everyday data science tasks using command-line tools

Jason Morris, Chris McCubbin, Raymond Page

The Command Line has been in existence on UNIX-based OSes in the form of Bash shell for over 3 decades. However, very little is known to developers as to how command-line tools can be OSEMN (pronounced as awesome and standing for Obtaining, Scrubbing, Exploring, Modeling, and iNterpreting data) for carrying out simple-to-advanced data science tasks at speed.This book will start with the requisite concepts and installation steps for carrying out data science tasks using the command line. You will learn to create a data pipeline to solve the problem of working with small-to medium-sized files on a single machine. You will understand the power of the command line, learn how to edit files using a text-based and an. You will not only learn how to automate jobs and scripts, but also learn how to visualize data using the command line. By the end of this book, you will learn how to speed up the process and perform automated tasks using command-line tools.

React 16 Tooling. Master essential cutting-edge tools, such as create-react-app, Jest, and Flow

Adam Boduch

React 16 Tooling covers the most important tools, utilities, and libraries that every React developer needs to know — in detail. As React has grown, the amazing toolset around it has also grown, adding features and enhancing the development workflow. Each of these essential tools is presented in a practical manner and in a logical order mirroring the development workflow. These tools will make your development life simpler and happier, enabling you to create better and more performant apps.Adam starts with a hand-picked selection of the best tools for the React 16 ecosystem. For starters, there’s the create-react-app utility that’s officially supported by the React team. Not only does this tool bootstrap your React project for you, it also provides a consistent and stable framework to build upon. The premise is that when you don’t have to think about meta development work, more focus goes into the product itself.Other React tools follow this same approach to automating and improving your development life. Jest makes unit testing quicker. Flow makes catching errors easier. Docker containers make deployment in a stack simpler. Storybook makes developing components straightforward. ESLint makes writing standardized code faster. The React DevTools plugin makes debugging a cinch. React 16 Tooling clears away the barriers so you can focus on developing the good parts. In this book, we’ll look at each of these powerful tools in detail, showing you how to build the perfect React ecosystem to develop your apps within.

Learning Concurrent Programming in Scala. Practical Multithreading in Scala - Second Edition

Aleksandar Prokopec

Scala is a modern, multiparadigm programming language designed to express common programming patterns in a concise, elegant, and type-safe way. Scala smoothly integrates the features of object-oriented and functional languages.In this second edition, you will find updated coverage of the Scala 2.12 platform. The Scala 2.12 series targets Java 8 and requires it for execution. The book starts by introducing you to the foundations of concurrent programming on the JVM, outlining the basics of the Java Memory Model, and then shows some of the classic building blocks of concurrency, such as the atomic variables, thread pools, and concurrent data structures, along with the caveats of traditional concurrency.The book then walks you through different high-level concurrency abstractions, each tailored toward a specific class of programming tasks, while touching on the latest advancements of async programming capabilities of Scala. It also covers some useful patterns and idioms to use with the techniques described. Finally, the book presents an overview of when to use which concurrency library and demonstrates how they all work together, and then presents new exciting approaches to building concurrent and distributed systems.Who this book is written forIf you are a Scala programmer with no prior knowledge of concurrent programming, or seeking to broaden your existing knowledge about concurrency, this book is for you. Basic knowledge of the Scala programming language will be helpful.

Hands-On Functional Programming in RUST. Build modular and reactive applications with functional programming techniques in Rust 2018

Andrew Johnson

Functional programming allows developers to divide programs into smaller, reusable components that ease the creation, testing, and maintenance of software as a whole. Combined with the power of Rust, you can develop robust and scalable applications that fulfill modern day software requirements. This book will help you discover all the Rust features that can be used to build software in a functional way.We begin with a brief comparison of the functional and object-oriented approach to different problems and patterns. We then quickly look at the patterns of control flow, data the abstractions of these unique to functional programming. The next part covers how to create functional apps in Rust; mutability and ownership, which are exclusive to Rust, are also discussed. Pure functions are examined next and you'll master closures, their various types, and currying. We also look at implementing concurrency through functional design principles and metaprogramming using macros. Finally, we look at best practices for debugging and optimization. By the end of the book, you will be familiar with the functional approach of programming and will be able to use these techniques on a daily basis.

Hands-On Transfer Learning with Python. Implement advanced deep learning and neural network models using TensorFlow and Keras

Dipanjan Sarkar, Raghav Bali, Tamoghna Ghosh

Transfer learning is a machine learning (ML) technique where knowledge gained during training a set of problems can be used to solve other similar problems. The purpose of this book is two-fold; firstly, we focus on detailed coverage of deep learning (DL) and transfer learning, comparing and contrasting the two with easy-to-follow concepts and examples. The second area of focus is real-world examples and research problems using TensorFlow, Keras, and the Python ecosystem with hands-on examples. The book starts with the key essential concepts of ML and DL, followed by depiction and coverage of important DL architectures such as convolutional neural networks (CNNs), deep neural networks (DNNs), recurrent neural networks (RNNs), long short-term memory (LSTM), and capsule networks. Our focus then shifts to transfer learning concepts, such as model freezing, fine-tuning, pre-trained models including VGG, inception, ResNet, and how these systems perform better than DL models with practical examples. In the concluding chapters, we will focus on a multitude of real-world case studies and problems associated with areas such as computer vision, audio analysis and natural language processing (NLP).By the end of this book, you will be able to implement both DL and transfer learning principles in your own systems.

Machine Learning with Swift. Artificial Intelligence for iOS

Alexander Sosnovshchenko, Oleksandr Baiev

Machine learning as a field promises to bring increased intelligence to the software by helping us learn and analyse information efficiently and discover certain patterns that humans cannot. This book will be your guide as you embark on an exciting journey in machine learning using the popular Swift language. We’ll start with machine learning basics in the first part of the book to develop a lasting intuition about fundamental machine learning concepts. We explore various supervised and unsupervised statistical learning techniques and how to implement them in Swift, while the third section walks you through deep learning techniques with the help of typical real-world cases. In the last section, we will dive into some hard core topics such as model compression, GPU acceleration and provide some recommendations to avoid common mistakes during machine learning application development. By the end of the book, you'll be able to develop intelligent applications written in Swift that can learn for themselves.