Getting Started with Gulp. Automating web development workflows - Second Edition

Travis Maynard

This book is a hands-on guide to get you up to speed with gulp. You will quickly learn how to install, configure, and run your own build system. It will instill you with the ability to automate several common development tasks to vastly improve your development workflow. This book first demonstrates various Gulp use cases before running through the steps of configuring, running, and customizing Gulp, providing you with core concepts of gulp, node.js, and npm. Diving a bit deeper into the gulp ecosystem, we will discuss when and why to use a node module instead of a gulp plugin. We will also go over a few issues that we can run into while using gulp and learn about ways to work around them to improve your gulp experience.By the end of this book, you will be able to create your very own gulp build from scratch, create and maintain tasks and project builds, and automate your workflow with plugins and custom tasks.

Mastering Proxmox. Build virtualized environments using the Proxmox VE hypervisor - Third Edition

Wasim Ahmed

Proxmox is an open source server virtualization solution that has enterprise-class features for managing virtual machines, for storage, and to virtualize both Linux and Windows application workloads.You'll begin with a refresher on the advanced installation features and the Proxmox GUI to familiarize yourself with the Proxmox VE hypervisor. Then, you'll move on to explore Proxmox under the hood, focusing on storage systems, such as Ceph, used with Proxmox. Moving on, you'll learn to manage KVM virtual machines, deploy Linux containers fast, and see how networking is handled in Proxmox. You'll also learn how to protect a cluster or a VM with a firewall and explore the new high availability features introduced in Proxmox VE 5.0. Next, you'll dive deeper into the backup/restore strategy and see how to properly update and upgrade a Proxmox node. Later, you'll learn how to monitor a Proxmox cluster and all of its components using Zabbix. Finally, you'll discover how to recover Promox from disaster strikes through some real-world examples. By the end of the book, you'll be an expert at making Proxmox work in production environments with minimal downtime.

Intelligent IoT Projects in 7 Days. Build exciting projects using smart devices

Agus Kurniawan

Intelligent IoT Projects in 7 days is about creating smart IoT projects in just 7 days. This book will help you to overcome the challenge of analyzing data from physical devices. This book aims to help you put together some of the most exciting IoT projects in a short span of time. You'll be able to use these in achieving or automating everyday tasks—one project per day.We will start with a simple smart gardening system and move on to a smart parking system, and then we will make our own vending machine, a smart digital advertising dashboard, a smart speaker machine, an autonomous fire fighter robot, and finally look at a multi-robot cooperation using swarm intelligence

Hands-On Markov Models with Python. Implement probabilistic models for learning complex data sequences using the Python ecosystem

Ankur Ankan, Abinash Panda

Hidden Markov Model (HMM) is a statistical model based on the Markov chain concept. Hands-On Markov Models with Python helps you get to grips with HMMs and different inference algorithms by working on real-world problems. The hands-on examples explored in the book help you simplify the process flow in machine learning by using Markov model concepts, thereby making it accessible to everyone.Once you’ve covered the basic concepts of Markov chains, you’ll get insights into Markov processes, models, and types with the help of practical examples. After grasping these fundamentals, you’ll move on to learning about the different algorithms used in inferences and applying them in state and parameter inference. In addition to this, you’ll explore the Bayesian approach of inference and learn how to apply it in HMMs.In further chapters, you’ll discover how to use HMMs in time series analysis and natural language processing (NLP) using Python. You’ll also learn to apply HMM to image processing using 2D-HMM to segment images. Finally, you’ll understand how to apply HMM for reinforcement learning (RL) with the help of Q-Learning, and use this technique for single-stock and multi-stock algorithmic trading.By the end of this book, you will have grasped how to build your own Markov and hidden Markov models on complex datasets in order to apply them to projects.

Spring Boot 2.0 Projects. Build production-grade reactive applications and microservices with Spring Boot

Mohamed Shazin Sadakath

Spring Boot is a lightweight framework that provides a set of tools to create production-grade applications and services. Spring Boot 2.0 Projects is a comprehensive project-based guide for those who are new to Spring, that will get you up to speed with building real-world projects. Complete with clear step-by-step instructions, these easy-to-follow tutorials demonstrate best practices and key insights into building efficient applications with Spring Boot. The book starts off by teaching you how to develop a web application using Spring Boot, followed by giving you an understanding of creating a Spring Boot-based simple blog management system that uses Elasticsearch as the data store. Next, you’ll build a RESTful web services application using Kotlin and the Spring WebFlux framework - a new framework that enables you to create reactive applications in a functional way. Toward the last few chapters, you will build a taxi-hailing API with reactive microservices using Spring Boot, in addition to developing a Twitter clone with the help of a Spring Boot backend. To build on your knowledge further, you’ll also learn how to construct an asynchronous email formatter.By the end of this book, you’ll have a firm foundation in Spring programming and understand how to build powerful, engaging applications in Java using the Spring Boot framework.

Statistics for Data Science. Leverage the power of statistics for Data Analysis, Classification, Regression, Machine Learning, and Neural Networks

James D. Miller

Data science is an ever-evolving field, which is growing in popularity at an exponential rate. Data science includes techniques and theories extracted from the fields of statistics; computer science, and, most importantly, machine learning, databases, data visualization, and so on.This book takes you through an entire journey of statistics, from knowing very little to becoming comfortable in using various statistical methods for data science tasks. It starts off with simple statistics and then move on to statistical methods that are used in data science algorithms. The R programs for statistical computation are clearly explained along with logic. You will come across various mathematical concepts, such as variance, standard deviation, probability, matrix calculations, and more. You will learn only what is required to implement statistics in data science tasks such as data cleaning, mining, and analysis. You will learn the statistical techniques required to perform tasks such as linear regression, regularization, model assessment, boosting, SVMs, and working with neural networks.By the end of the book, you will be comfortable with performing various statistical computations for data science programmatically.

Hands-on Design Patterns with Kotlin. Build scalable applications using traditional, reactive, and concurrent design patterns in Kotlin

Alexey Soshin

Design patterns enable you as a developer to speed up the development process by providing you with proven development paradigms. Reusing design patterns helps prevent complex issues that can cause major problems, improves your code base, promotes code reuse, and makes an architecture more robust.The mission of this book is to ease the adoption of design patterns in Kotlin and provide good practices for programmers. The book begins by showing you the practical aspects of smarter coding in Kotlin, explaining the basic Kotlin syntax and the impact of design patterns. From there, the book provides an in-depth explanation of the classical design patterns of creational, structural, and behavioral families, before heading into functional programming. It then takes you through reactive and concurrent patterns, teaching you about using streams, threads, and coroutines to write better code along the way By the end of the book, you will be able to efficiently address common problems faced while developing applications and be comfortable working on scalable and maintainable projects of any size.

Kali Linux Wireless Penetration Testing Cookbook. Identify and assess vulnerabilities present in your wireless network, Wi-Fi, and Bluetooth enabled devices to improve your wireless security

Sean-Philip Oriyano

More and more organizations are moving towards wireless networks, and Wi-Fi is a popular choice. The security of wireless networks is more important than ever before due to the widespread usage of Wi-Fi networks. This book contains recipes that will enable you to maximize the success of your wireless network testing using the advanced ethical hacking features of Kali Linux. This book will go through techniques associated with a wide range of wireless penetration tasks, including WLAN discovery scanning, WEP cracking, WPA/WPA2 cracking, attacking access point systems, operating system identification, vulnerability mapping, and validation of results. You will learn how to utilize the arsenal of tools available in Kali Linux to penetrate any wireless networking environment. You will also be shown how to identify remote services, how to assess security risks, and how various attacks are performed. By finishing the recipes, you will feel confident conducting wireless penetration tests and will be able to protect yourself or your organization from wireless security threats.