Become a better web programmer by writing efficient and modular code using ES6 and ES8 About This Book ? Learn to write asynchronous code and improve the readability of your web applications ? Explore advanced concepts such as closures, Proxy, generators, Promise, async functions, and Atomics ? Use different design patterns to create structures to solve common organizational and processing issues Who This Book Is For If you’re a web developer with a basic understanding of JavaScript and wish to learn the latest features of ECMAScript for developing efficient web applications, this book is for you. What You Will Learn ? Organize JavaScript programs across multiple files, using ES modules ? Create and work with promises using the Promise object and methods ? Compose async functions to propagate and handle errors ? Solve organizational and processing issues with structures using design patterns ? Use classes to encapsulate and share behavior ? Orchestrate parallel programs using WebWorkers, SharedMemory, and Atomics ? Use and extend Map, Set, and Symbol to work with user-defined classes and simulate data types ? Explore new array methods to avoid looping with arrays and other collections In Detail ECMAScript Cookbook follows a modular approach with independent recipes covering different feature sets and specifications of ECMAScript to help you become an efficient programmer. This book starts off with organizing your JavaScript applications as well as delivering those applications to modem and legacy systems. You will get acquainted with features of ECMAScript 8 such as async, SharedArrayBuffers, and Atomic operations that enhance asynchronous and parallel operations. In addition to this, this book will introduce you to SharedArrayBuffers, which allow web workers to share data directly, and Atomic operations, which help coordinate behavior across the threads. You will also work with OOP and Collections, followed by new functions and methods on the built-in Object and Array types that make common operations more manageable and less error-prone. You will then see how to easily build more sophisticated and expressive program structures with classes and inheritance. In the end, we will cover Sets, Maps, and Symbols, which are the new types introduced in ECMAScript 6 to add new behaviors and allow you to create simple and powerful modules. By the end of the book, you will be able to produce more efficient, expressive, and simpler programs using the new features of ECMAScript. Style and approach This book will follow a modular approach covering independent recipes on different features of ECMAScript throughout the book.

A comprehensive guide to design, build and execute effective Big Data strategies using Hadoop About This Book ? Get an in-depth view of the Apache Hadoop ecosystem and an overview of the architectural patterns pertaining to the popular Big Data platform ? Conquer different data processing and analytics challenges using a multitude of tools such as Apache Spark, Elasticsearch, Tableau and more ? A comprehensive, step-by-step guide that will teach you everything you need to know, to be an expert Hadoop Architect Who This Book Is For This book is for Big Data professionals who want to fast-track their career in the Hadoop industry and become an expert Big Data architect. Project managers and mainframe professionals looking forward to build a career in Big Data Hadoop will also find this book to be useful. Some understanding of Hadoop is required to get the best out of this book. What You Will Learn ? Build an efficient enterprise Big Data strategy centered around Apache Hadoop ? Gain a thorough understanding of using Hadoop with various Big Data frameworks such as Apache Spark, Elasticsearch and more ? Set up and deploy your Big Data environment on premises or on the cloud with Apache Ambari ? Design effective streaming data pipelines and build your own enterprise search solutions ? Utilize the historical data to build your analytics solutions and visualize them using popular tools such as Apache Superset ? Plan, set up and administer your Hadoop cluster efficiently In Detail The complex structure of data these days requires sophisticated solutions for data transformation, to make the information more accessible to the users.This book empowers you to build such solutions with relative ease with the help of Apache Hadoop, along with a host of other Big Data tools. This book will give you a complete understanding of the data lifecycle management with Hadoop, followed by modeling of structured and unstructured data in Hadoop. It will also show you how to design real-time streaming pipelines by leveraging tools such as Apache Spark, and build efficient enterprise search solutions using Elasticsearch. You will learn to build enterprise-grade analytics solutions on Hadoop, and how to visualize your data using tools such as Apache Superset. This book also covers techniques for deploying your Big Data solutions on the cloud Apache Ambari, as well as expert techniques for managing and administering your Hadoop cluster. By the end of this book, you will have all the knowledge you need to build expert Big Data systems. Style and approach Comprehensive guide with a perfect blend of theory, examples and implementation of real-world use-cases

This fast-paced guide will quickly enhance your skills to develop a highly scalable Cloud environment About This Book ? Efficiently build a highly scalable and reliable cloud environment for your applications with AWS ? Leverage the various AWS components and services to build a secure, reliable, and robust environment to host your applications on ? This quick-start guide will quickly enhance your skills to develop highly scalable services Who This Book Is For This book is for IT professionals and system administrators looking to design, deploy, and manage your applications and services on the AWS cloud platform. It’s also ideal for developers looking to build highly scalable cloud-based services. A basic understanding of AWS would be beneficial. What You Will Learn ? Find out about IAM to access AWS services securely ? Explore EC2 (virtual server) and scale up/down your application based on heavy traffic ? Learn about unlimited data storage service S3 and host a static website within minutes ? Get to grips with Relational Databases and NoSQL databases under the AWS ecosystem ? Understand the caching mechanism ? Get to know about notifications service and monitor AWS services ? Secure and troubleshoot your AWS architecture In Detail AWS is at the forefront of Cloud Computing today. Businesses are adopting AWS Cloud because of its reliability, versatility, and flexible design. The main focus of this book is teaching you how to build and manage highly reliable and scalable applications and services on AWS. It will provide you with all the necessary skills to design, deploy, and manage your applications and services on the AWS cloud platform. We’ll start by exploring Amazon S3, EC2, and so on to get you well-versed with core Amazon services. Moving on, we’ll teach you how to design and deploy highly scalable and optimized workloads. You’ll also discover easy-to-follow, hands-on steps, tips, and recommendations throughout the book and get to know essential security and troubleshooting concepts. By the end of the book, you’ll be able to create a highly secure, fault tolerant, and scalable environment for your applications to run on. Style and approach This book is all about fast and intensive learning. That means we don’t waste time helping you get started. The new features provided by AWS resources are being covered with highly-effective examples to develop new things, demonstrating different ways to create and use the AWS resources efficiently.

Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of TensorFlow v1.7. About This Book ? Learn how to implement advanced techniques in deep learning with Google's brainchild, TensorFlow v1.7 ? Explore deep neural networks and layers of data abstraction with the help of this comprehensive guide ? Gain real-world contextualization through some deep learning problems concerning research and application Who This Book Is For The book is for people interested in machine learning and machine intelligence. A rudimentary level of programming in one language is assumed, as is a basic familiarity with computer science techniques and technologies, including a basic awareness of computer hardware and algorithms. Some competence in mathematics is needed to the level of elementary linear algebra and calculus. What You Will Learn ? Apply deep machine intelligence and GPU computing with TensorFlow v1.7 ? Access public datasets and use TensorFlow to load, process, and transform the data ? Discover how to use the high-level TensorFlow API to build more powerful applications ? Use deep learning for scalable object detection and mobile computing ? Train machines quickly to learn from data by exploring reinforcement learning techniques ? Explore active areas of deep learning research and applications In Detail Deep learning is a branch of machine learning algorithms based on learning multiple levels of abstraction. Neural networks, which are at the core of deep learning, are being used in predictive analytics, computer vision, natural language processing, time series forecasting, and to perform a myriad of other complex tasks. This book is conceived for developers, data analysts, machine learning practitioners and deep learning enthusiasts who want to build powerful, robust, and accurate predictive models with the power of TensorFlow v1.7, combined with other open source Python libraries. Throughout the book, you’ll learn how to develop deep learning applications for machine learning systems using Feedforward Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Autoencoders, and Factorization Machines. Discover how to attain deep learning programming on GPU in a distributed way. You'll come away with an in-depth knowledge of machine learning techniques and the skills to apply them to real-world projects. Style and approach This step-by-step guide explores common, and not so common, deep neural networks, and shows how they can be exploited in the real world with complex raw data. Benefit from practical examples, and learn how to implement different types of neural nets to build smart applications related to text, speech, and image data processing.

Build your own hybrid cloud strategy with this comprehensive learning guide. About This Book ? Build a hybrid cloud strategy for your organization with AWS and OpenStack ? Leverage Hybrid Cloud to design a complex deployment pipeline ? Learn to implement security and monitoring best practices with real-world examples Who This Book Is For This book is targeted at cloud architects, cloud solution providers, DevOps engineers, or any working stakeholder who wants to learn about the hybrid cloud architecture. A basic understanding of public and private cloud is desirable. What You Will Learn ? Learn the demographics and definitions of Hybrid Cloud ? Understand the different architecture and design of Hybrid Cloud ? Explore multi-cloud strategy and use it with your hybrid cloud ? Implement a Hybrid Cloud using CMP / Common API’s ? Implement a Hybrid Cloud using Containers ? Overcome various challenges and issues while working with your Hybrid Cloud ? Understand how to monitor your Hybrid Cloud ? Discover the security implications in the Hybrid Cloud In Detail Hybrid cloud is currently the buzz word in the cloud world. Organizations are planning to adopt hybrid cloud strategy due to its advantages such as untested workloads, cloud-bursting, cloud service brokering and so on. This book will help you understand the dynamics, design principles, and deployment strategies of a Hybrid Cloud. You will start by understanding the concepts of hybrid cloud and the problems it solves as compared to a stand-alone public and private cloud. You will be delving into the different architecture and design of hybrid cloud. The book will then cover advanced concepts such as building a deployment pipeline, containerization strategy, and data storage mechanism. Next up, you will be able to deploy an external CMP to run a Hybrid cloud and integrate it with your OpenStack and AWS environments. You will also understand the strategy for designing a Hybrid Cloud using containerization and work with pre-built solutions like vCloud Air, VMware for AWS, and Azure Stack. Finally, the book will cover security and monitoring related best practices that will help you secure your cloud infrastructure. By the end of the book, you will be in a position to build a hybrid cloud strategy for your organization. Style and approach This book follows a step-by-step, practical approach to deploying and implementing hybrid cloud architectures using AWS and OpenStack.

Build neural network models in text, vision and advanced analytics using PyTorch About This Book ? Learn PyTorch for implementing cutting-edge deep learning algorithms. ? Train your neural networks for higher speed and flexibility and learn how to implement them in various scenarios; ? Cover various advanced neural network architecture such as ResNet, Inception, DenseNet and more with practical examples; Who This Book Is For This book is for machine learning engineers, data analysts, data scientists interested in deep learning and are looking to explore implementing advanced algorithms in PyTorch. Some knowledge of machine learning is helpful but not a mandatory need. Working knowledge of Python programming is expected. What You Will Learn ? Use PyTorch for GPU-accelerated tensor computations ? Build custom datasets and data loaders for images and test the models using torchvision and torchtext ? Build an image classifier by implementing CNN architectures using PyTorch ? Build systems that do text classification and language modeling using RNN, LSTM, and GRU ? Learn advanced CNN architectures such as ResNet, Inception, Densenet, and learn how to use them for transfer learning ? Learn how to mix multiple models for a powerful ensemble model ? Generate new images using GAN’s and generate artistic images using style transfer In Detail Deep learning powers the most intelligent systems in the world, such as Google Voice, Siri, and Alexa. Advancements in powerful hardware, such as GPUs, software frameworks such as PyTorch, Keras, Tensorflow, and CNTK along with the availability of big data have made it easier to implement solutions to problems in the areas of text, vision, and advanced analytics. This book will get you up and running with one of the most cutting-edge deep learning libraries—PyTorch. PyTorch is grabbing the attention of deep learning researchers and data science professionals due to its accessibility, efficiency and being more native to Python way of development. You'll start off by installing PyTorch, then quickly move on to learn various fundamental blocks that power modern deep learning. You will also learn how to use CNN, RNN, LSTM and other networks to solve real-world problems. This book explains the concepts of various state-of-the-art deep learning architectures, such as ResNet, DenseNet, Inception, and Seq2Seq, without diving deep into the math behind them. You will also learn about GPU computing during the course of the book. You will see how to train a model with PyTorch and dive into complex neural networks such as generative networks for producing text and images. By the end of the book, you'll be able to implement deep learning applications in PyTorch with ease. Style and approach An end-to-end guide that teaches you all about PyTorch and how to implement it in various scenarios.

Learn how to automate and manage your containers and reduce the overall operation burden on your system. About This Book ? Use containers to manage, scale and orchestrate apps in your organization ? Transform the latest concept of Kubernetes 1.10 into examples ? Expert techniques for orchestrating containers effectively Who This Book Is For This book is for system administrators, developers, DevOps engineers, or any stakeholder who wants to understand how Kubernetes works using a recipe-based approach. Basic knowledge of Kubernetes and Containers is required. What You Will Learn ? Build your own container cluster ? Deploy and manage highly scalable, containerized applications with Kubernetes ? Build high-availability Kubernetes clusters ? Build a continuous delivery pipeline for your application ? Track metrics and logs for every container running in your cluster ? Streamline the way you deploy and manage your applications with large-scale container orchestration In Detail Kubernetes is an open source orchestration platform to manage containers in a cluster environment. With Kubernetes, you can configure and deploy containerized applications easily. This book gives you a quick brush up on how Kubernetes works with containers, and an overview of main Kubernetes concepts, such as Pods, Deployments, Services and etc. This book explains how to create Kubernetes clusters and run applications with proper authentication and authorization configurations. With real-world recipes, you'll learn how to create high availability Kubernetes clusters on AWS, GCP and in on-premise datacenters with proper logging and monitoring setup. You'll also learn some useful tips about how to build a continuous delivery pipeline for your application. Upon completion of this book, you will be able to use Kubernetes in production and will have a better understanding of how to manage containers using Kubernetes. Style and approach This recipe-based book will teach you how to use Kubernetes in production and will help you discover various steps involved in managing your containers using Kubernetes

Be an adaptive thinker that leads the way to Artificial Intelligence About This Book ? AI-based examples to guide you in designing and implementing machine intelligence ? Develop your own method for future AI solutions ? Acquire advanced AI, machine learning, and deep learning design skills Who This Book Is For Artificial Intelligence by Example is a simple, explanatory, and descriptive guide for junior developers, experienced developers, technology consultants, and those interested in AI who want to understand the fundamentals of Artificial Intelligence and implement it practically by devising smart solutions. Prior experience with Python and statistical knowledge is essential to make the most out of this book. What You Will Learn ? Use adaptive thinking to solve real-life AI case studies ? Rise beyond being a modern-day factory code worker ? Acquire advanced AI, machine learning, and deep learning designing skills ? Learn about cognitive NLP chatbots, quantum computing, and IoT and blockchain technology ? Understand future AI solutions and adapt quickly to them ? Develop out-of-the-box thinking to face any challenge the market presents In Detail Artificial Intelligence has the potential to replicate humans in every field. This book serves as a starting point for you to understand how AI is built, with the help of intriguing examples and case studies. Artificial Intelligence By Example will make you an adaptive thinker and help you apply concepts to real-life scenarios. Using some of the most interesting AI examples, right from a simple chess engine to a cognitive chatbot, you will learn how to tackle the machine you are competing with. You will study some of the most advanced machine learning models, understand how to apply AI to blockchain and IoT, and develop emotional quotient in chatbots using neural networks. You will move on to designing AI solutions in a simple manner rather than get confused by complex architectures and techniques. This comprehensive guide will be a starter kit for you to develop AI applications on your own. By the end of this book, will have understood the fundamentals of AI and worked through a number of case studies that will help you develop business vision. Style and approach An easy-to-follow step by step guide which will help you get to grips with real world application of Artificial Intelligence

Learn how to execute web application penetration testing end-to-end About This Book ? Build an end-to-end threat model landscape for web application security ? Learn both web application vulnerabilities and web intrusion testing ? Associate network vulnerabilities with a web application infrastructure Who This Book Is For Practical Web Penetration Testing is for you if you are a security professional, penetration tester, or stakeholder who wants to execute penetration testing using the latest and most popular tools. Basic knowledge of ethical hacking would be an added advantage. What You Will Learn ? Learn how to use Burp Suite effectively ? Use Nmap, Metasploit, and more tools for network infrastructure tests ? Practice using all web application hacking tools for intrusion tests using Kali Linux ? Learn how to analyze a web application using application threat modeling ? Know how to conduct web intrusion tests ? Understand how to execute network infrastructure tests ? Master automation of penetration testing functions for maximum efficiency using Python In Detail Companies all over the world want to hire professionals dedicated to application security. Practical Web Penetration Testing focuses on this very trend, teaching you how to conduct application security testing using real-life scenarios. To start with, you’ll set up an environment to perform web application penetration testing. You will then explore different penetration testing concepts such as threat modeling, intrusion test, infrastructure security threat, and more, in combination with advanced concepts such as Python scripting for automation. Once you are done learning the basics, you will discover end-to-end implementation of tools such as Metasploit, Burp Suite, and Kali Linux. Many companies deliver projects into production by using either Agile or Waterfall methodology. This book shows you how to assist any company with their SDLC approach and helps you on your journey to becoming an application security specialist. By the end of this book, you will have hands-on knowledge of using different tools for penetration testing. Style and approach In this book, you will learn and understand the workflow of application security testing. Starting from analysis using threat modeling until the testing phase and before the web project goes into production, you will be able conduct effective penetrating testing using web intrusion tests , network infrastructure tests, and code review.

Optimize the powerful techniques of Java 9 to boost your application's performance About This Book ? Tackle all kinds of performance-related issues and streamline your development ? Dive into the new features of Java 9 ? Implement highly efficient and reliable codes with the help of new APIs of Java ? Embedded with assessments that will help you revise the concepts you have learned in this book Who This Book Is For This book is targeted at developers who would like to build reliable and high-performance applications with Java. What You Will Learn ? Familiarize with modular development and its impact on performance ? Learn various string-related performance improvements, including compact string and modify string concatenation ? Explore various underlying compiler improvements, such as tiered attribution and Ahead-of-Time (AOT) compilation ? Learn security manager improvements ? Understand enhancements in graphics rasterizers ? Use of command-line tools to speed up application development ? Learn how to implement multithreading and reactive programming ? Build microservices in Java 9 ? Implement APIs to improve application code In Detail Java 9 which is one of the most popular application development languages. The latest released version Java 9 comes with a host of new features and new APIs with lots of ready to use components to build efficient and scalable applications. Streams, parallel and asynchronous processing, multithreading, JSON support, reactive programming, and microservices comprise the hallmark of modern programming and are now fully integrated into the JDK. This book focuses on providing quick, practical solutions to enhance your application's performance. You will explore the new features, APIs, and various tools added in Java 9 that help to speed up the development process. You will learn about jshell, Ahead-of-Time (AOT) compilation, and the basic threads related topics including sizing and synchronization. You will also explore various strategies for building microservices including container-less, self-contained, and in-container. This book is ideal for developers who would like to build reliable and high-performance applications with Java. This book is embedded with useful assessments that will help you revise the concepts you have learned in this book. Style and approach This book is a fast-paced guide that provides practical solutions to enhance your application’s performance. Note: This book is a blend of text and quizzes, all packaged up keeping your journey in mind. It includes content from the following Packt product: ? Java 9 High Performance by Mayur Ramgir and Nick Samoylov

Delve deep into various security aspects of AWS to build and maintain a secured environment About This Book ? Learn to secure your network, infrastructure, data, and applications in AWS cloud ? Use AWS managed security services to automate security ? Dive deep into various aspects such as the security model, compliance, access management and much more to build and maintain a secured environment ? Explore Cloud Adoption Framework (CAF) and its components ? Embedded with assessments that will help you revise the concepts you have learned in this book Who This Book Is For This book is for all IT professionals, system administrators, security analysts, solution architects, and chief information security officers who are responsible for securing workloads in AWS for their organizations. What You Will Learn ? Get familiar with VPC components, features, and benefits ? Learn to create and secure your private network in AWS ? Explore encryption and decryption fundamentals ? Understand monitoring, logging, and auditing in AWS ? Ensure data security in AWS ? Secure your web and mobile applications in AWS ? Learn security best practices for IAM, VPC, shared security responsibility model, and so on In Detail With organizations moving their workloads, applications, and infrastructure to the cloud at an unprecedented pace, security of all these resources has been a paradigm shift for all those who are responsible for security; experts, novices, and apprentices alike. This book focuses on using native AWS security features and managed AWS services to help you achieve continuous security. Starting with an introduction to Virtual Private Cloud (VPC) to secure your AWS VPC, you will quickly explore various components that make up VPC such as subnets, security groups, various gateways, and many more. You will also learn to protect data in the AWS platform for various AWS services by encrypting and decrypting data in AWS. You will also learn to secure web and mobile applications in AWS cloud. This book is ideal for all IT professionals, system administrators, security analysts, solution architects, and chief information security officers who are responsible for securing workloads in AWS for their organizations. This book is embedded with useful assessments that will help you revise the concepts you have learned in this book. Style and approach This book follows a practical approach delving into different aspects of AWS security. It focuses on using native AWS security features and managed AWS services to help you achieve continuous security. Note: This book is a blend of text and quizzes, all packaged up keeping your journey in mind. It includes content from the following Packt product: ? Mastering AWS Security by Albert Anthony

Unlock the power of Spring Boot to build and deploy production-ready microservices About This Book ? Get to know the advanced features of Spring Boot in order to develop and monitor applications ? Use Spring cloud to deploy and manage microservices on the cloud ? Look at embedded servers and deploy a test application to a PaaS Cloud platform ? Embedded with assessments that will help you revise the concepts you have learned in this book Who This Book Is For This book is aimed at Java developers who knows the basics of Spring programming and want to build microservices with Spring Boot. What You Will Learn ? Use Spring Initializr to create a basic spring project ? Build a basic microservice with Spring Boot ? Implement caching and exception handling ? Secure your microservice with Spring security and OAuth2 ? Deploy microservices using self-contained HTTP server ? Monitor your microservices with Spring Boot actuator ? Learn to develop more effectively with developer tools In Detail Microservices helps in decomposing applications into small services and move away from a single monolithic artifact. It helps in building systems that are scalable, flexible, and high resilient. Spring Boot helps in building REST-oriented, production-grade microservices. This book is a quick learning guide on how to build, monitor, and deploy microservices with Spring Boot. You'll be first familiarized with Spring Boot before delving into building microservices. You will learn how to document your microservice with the help of Spring REST docs and Swagger documentation. You will then learn how to secure your microservice with Spring Security and OAuth2. You will deploy your app using a self-contained HTTP server and also learn to monitor a microservice with the help of Spring Boot actuator. This book is ideal for Java developers who knows the basics of Spring programming and want to build microservices with Spring Boot. This book is embedded with useful assessments that will help you revise the concepts you have learned in this book. Style and approach This book follows a practical approach to teach you how to build, monitor, and deploy microservices with Spring Boot. Note: This book is a blend of text and quizzes, all packaged up keeping your journey in mind. It includes content from the following Packt product: ? Mastering Spring 5.0 by Ranga Rao Karanam

Build applications and infrastructures that leverage Function-as-a-Service and Docker About This Book ? Implement containerization in Serverless/FaaS environments ? Utilize Docker as a functional unit of work for Serverless/FaaS platforms ? Use Docker as a portable infrastructure for Serverless Applications Who This Book Is For If you are a Developer, a Docker Engineer, a DevOps Engineer, or any stakeholder interested in learning the use of Docker on Serverless environments then this book is for you. What You Will Learn ? Learn what Serverless and FaaS applications are ? Get acquainted with the architectures of three major serverless systems ? Explore how Docker technologies can help develop Serverless applications ? Create and maintain FaaS infrastructures ? Set up Docker infrastructures to serve as on-premises FaaS infrastructures ? Define functions for Serverless applications with Docker containers In Detail Serverless applications have gained a lot of popularity among developers and are currently the buzzwords in the tech market. Docker and serverless are two terms that go hand-in-hand. This book will start by explaining serverless and Function-as-a-Service (FaaS) concepts, and why they are important. Then, it will introduce the concepts of containerization and how Docker fits into the Serverless ideology. It will explore the architectures and components of three major Docker-based FaaS platforms, how to deploy and how to use their CLI. Then, this book will discuss how to set up and operate a production-grade Docker cluster. We will cover all concepts of FaaS frameworks with practical use cases, followed by deploying and orchestrating these serverless systems using Docker. Finally, we will also explore advanced topics and prototypes for FaaS architectures in the last chapter. By the end of this book, you will be in a position to build and deploy your own FaaS platform using Docker. Style and approach A practical guide that offers a simple way to easily understand Serverless Applications utilizing Docker as the development environment.

Enhance your software deployment workflow using containers About This Book ? Get up-and-running with basic to advanced concepts of Docker ? Get acquainted with concepts such as Docker containers, Docker images, orchestrators and so on. ? Practical test-based approach to learning a prominent containerization tool Who This Book Is For This book is targeted at system administrators, operations engineers, DevOps engineers, and developers or stakeholders who are interested in getting started with Docker from scratch. No prior experience with Docker Containers is required. What You Will Learn ? Containerize your traditional or microservice-based application ? Share or ship your application as an immutable container image ? Build a Docker swarm and a Kubernetes cluster in the cloud ? Run a highly distributed application using Docker Swarm or Kubernetes ? Update or rollback a distributed application with zero downtime ? Secure your applications via encapsulation, networks, and secrets ? Know your options when deploying your containerized app into the cloud In Detail Docker containers have revolutionized the software supply chain in small and big enterprises. Never before has a new technology so rapidly penetrated the top 500 enterprises worldwide. Companies that embrace containers and containerize their traditional mission-critical applications have reported savings of at least 50% in total maintenance cost and a reduction of 90% (or more) of the time required to deploy new versions of those applications. Furthermore they are benefitting from increased security just by using containers as opposed to running applications outside containers. This book starts from scratch, introducing you to Docker fundamentals and setting up an environment to work with it. Then we delve into concepts such as Docker containers, Docker images, Docker Compose, and so on. We will also cover the concepts of deployment, orchestration, networking, and security. Furthermore, we explain Docker functionalities on public clouds such as AWS. By the end of this book, you will have hands-on experience working with Docker containers and orchestrators such as SwarmKit and Kubernetes. Style and approach The simple end-to-end guide will help you learn everything about how to containerize, ship, and run both a traditional application and a modern microservice-based application on-premise or in the cloud.

Practical, hands-on solutions in Python to overcome any problem in Machine Learning About This Book ? Master the advanced concepts, methodologies, and use cases of machine learning ? Build ML applications for analytics, NLP and computer vision domains ? Solve the most common problems in building machine learning models Who This Book Is For This book is for the intermediate users such as machine learning engineers, data engineers, data scientists, and more, who want to solve simple to complex machine learning problems in their day-to-day work and build powerful and efficient machine learning models. A basic understanding of the machine learning concepts and some experience with Python programming is all you need to get started with this book. What You Will Learn ? Select the right algorithm to derive the best solution in ML domains ? Perform predictive analysis effciently using ML algorithms ? Predict stock prices using the stock index value ? Perform customer analytics for an e-commerce platform ? Build recommendation engines for various domains ? Build NLP applications for the health domain ? Build language generation applications using different NLP techniques ? Build computer vision applications such as facial emotion recognition In Detail Machine learning (ML) helps you find hidden insights from your data without the need for explicit programming. This book is your key to solving any kind of ML problem you might come across in your job. You’ll encounter a set of simple to complex problems while building ML models, and you'll not only resolve these problems, but you’ll also learn how to build projects based on each problem, with a practical approach and easy-to-follow examples. The book includes a wide range of applications: from analytics and NLP, to computer vision domains. Some of the applications you will be working on include stock price prediction, a recommendation engine, building a chat-bot, a facial expression recognition system, and many more. The problem examples we cover include identifying the right algorithm for your dataset and use cases, creating and labeling datasets, getting enough clean data to carry out processing, identifying outliers, overftting datasets, hyperparameter tuning, and more. Here, you'll also learn to make more timely and accurate predictions. In addition, you'll deal with more advanced use cases, such as building a gaming bot, building an extractive summarization tool for medical documents, and you'll also tackle the problems faced while building an ML model. By the end of this book, you'll be able to fine-tune your models as per your needs to deliver maximum productivity. Style and approach This book is a step-by-step guide on how to develop machine learning applications for various domains. Each chapter of this book contains the practical guide on how to build specific machine learning applications from its base-line approach to the best possible approach. Basic necessary concepts, conman mistakes for every approach and optimization techniques are discussed for each application.

Build rich and collaborative applications using client-side code with React, Redux, and Firebase About This Book ? A practical guide covering the full stack for web development with React 16 and Firebase ? Leverage the power of Firebase Cloud Storage, messaging, functions, OAuth, and database security to develop serverless web applications. ? Develop high-performance applications without the hassle of setting up complex web infrastructure. Who This Book Is For This book is for JavaScript developers who have some previous knowledge of React and want to develop serverless, full-stack applications but without the hassle of setting up a complex infrastructure. What You Will Learn ? Install powerful React.js and Firebase tools to make development much more efficient ? Create React components with Firebase to save and retrieve the data in real-time ? Use Firebase Authentication to make your React user interface secure ? Develop React and Firebase applications with Redux integration ? Firebase database security rules ? Firebase Cloud Storage Integration to upload and store data on the cloud ? Create a complete real-time application with React and firebase ? Using Firebase Cloud messaging and Cloud functions with React ? Firebase Cloud Storage integration with React In Detail ReactJS is a wonderful framework for UI development. Firebase as a backend with React is a great choice as it is easy, powerful, and provides great developer experience. It removes a lot of boilerplate code from your app and allows you to focus on your app to get it out quickly to users. Firebase with React is also a good choice for Most Viable Product (MVP) development. This book provides more practical insights rather than just theoretical concepts and includes basic to advanced examples – from hello world to a real-time seat booking app and Helpdesk application This book will cover the essentials of Firebase and React.js and will take you on a fast-paced journey through building real-time applications with Firebase features such as Cloud Storage, Cloud Function, Hosting and the Realtime Database. We will learn how to secure our application by using Firebase authentication and database security rules. We will leverage the power of Redux to organize data in the front-end, since Redux attempts to make state mutations predictable by imposing certain restrictions on how and when updates can happen. Towards the end of the book you will have improved your React skills by realizing the potential of Firebase to create real-time serverless web applications. Style and approach Practical insights rather than just theoretical concepts while including basic to advanced examples – from hello world to a real-time seat booking app and Helpdesk application.

Combine the power of analytics and cloud computing for faster and efficient insights About This Book ? Master the concept of analytics on the cloud: and how organizations are using it ? Learn the design considerations and while applying a cloud analytics solution ? Design an end-to-end analytics pipeline on the cloud Who This Book Is For This book is targeted at CIOs, CTOs, and even analytics professionals looking for various alternatives to implement their analytics pipeline on the cloud. Data professionals looking to get started with cloud-based analytics will also find this book useful. Some basic exposure to cloud platforms such as GCP will be helpful, but not mandatory. What You Will Learn ? Explore the basics of cloud analytics and the major cloud solutions ? Learn how organizations are using cloud analytics to improve the ROI ? Explore the design considerations while adopting cloud services ? Work with the ingestion and storage tools of GCP such as Cloud Pub/Sub ? Process your data with tools such as Cloud Dataproc, BigQuery, etc ? Over 70 GCP tools to build an analytics engine for cloud analytics ? Implement machine learning and other AI techniques on GCP In Detail With the ongoing data explosion, more and more organizations all over the world are slowly migrating their infrastructure to the cloud. These cloud platforms also provide their distinct analytics services to help you get faster insights from your data. This book will give you an introduction to the concept of analytics on the cloud, and the different cloud services popularly used for processing and analyzing data. If you’re planning to adopt the cloud analytics model for your business, this book will help you understand the design and business considerations to be kept in mind, and choose the best tools and alternatives for analytics, based on your requirements. The chapters in this book will take you through the 70+ services available in Google Cloud Platform and their implementation for practical purposes. From ingestion to processing your data, this book contains best practices on building an end-to-end analytics pipeline on the cloud by leveraging popular concepts such as machine learning and deep learning. By the end of this book, you will have a better understanding of cloud analytics as a concept as well as a practical know-how of its implementation Style and approach Comprehensive guide with a perfect blend of theory, examples, and implementation of real-world use-cases

Grasp the fundamental concepts of deep learning using Tensorflow in a hands-on manner About This Book ? Get a first-hand experience of the deep learning concepts and techniques with this easy-to-follow guide ? Train different types of neural networks using Tensorflow for real-world problems in language processing, computer vision, transfer learning, and more ? Designed for those who believe in the concept of 'learn by doing', this book is a perfect blend of theory and code examples Who This Book Is For This book targets data scientists and machine learning developers who wish to get started with deep learning. If you know what deep learning is but are not quite sure of how to use it, this book will help you as well. An understanding of statistics and data science concepts is required. Some familiarity with Python programming will also be beneficial. What You Will Learn ? Understand the fundamentals of deep learning and how it is different from machine learning ? Get familiarized with Tensorflow, one of the most popular libraries for advanced machine learning ? Increase the predictive power of your model using feature engineering ? Understand the basics of deep learning by solving a digit classification problem of MNIST ? Demonstrate face generation based on the CelebA database, a promising application of generative models ? Apply deep learning to other domains like language modeling, sentiment analysis, and machine translation In Detail Deep learning is a popular subset of machine learning, and it allows you to build complex models that are faster and give more accurate predictions. This book is your companion to take your first steps into the world of deep learning, with hands-on examples to boost your understanding of the topic. This book starts with a quick overview of the essential concepts of data science and machine learning which are required to get started with deep learning. It introduces you to Tensorflow, the most widely used machine learning library for training deep learning models. You will then work on your first deep learning problem by training a deep feed-forward neural network for digit classification, and move on to tackle other real-world problems in computer vision, language processing, sentiment analysis, and more. Advanced deep learning models such as generative adversarial networks and their applications are also covered in this book. By the end of this book, you will have a solid understanding of all the essential concepts in deep learning. With the help of the examples and code provided in this book, you will be equipped to train your own deep learning models with more confidence. Style and approach A step-by-step guide filled with multiple examples to help you get started with data science and deep learning.

Leverage the power of Redis 4.x to develop, optimize and administer your Redis solutions with ease About This Book ? Build, deploy and administer high performance and scalable applications in Redis ? Covers a range of important tasks - including development and administration of Redis ? A practical guide that takes your understanding of Redis to the next level Who This Book Is For This book is for database administrators, developers and architects who want to tackle the common and not so common problems associated with the different development and administration-related tasks in Redis. A fundamental understanding of Redis is expected to get the best out of this book. What You Will Learn ? Install and configure your Redis instance ? Explore various data types and commands in Redis ? Build client-side applications as well as a Big Data framework with Redis ? Manage data replication and persistence in Redis ? Implement high availability and data sharding in Redis ? Extend Redis with Redis Module ? Benchmark, debug, fine-tune and troubleshoot various issues in Redis In Detail Redis is considered the world's most popular key-value store database. Its versatility and the wide variety of use cases it enables have made it a popular choice of database for many enterprises. Based on the latest version of Redis, this book provides both step-by-step recipes and relevant the background information required to utilize its features to the fullest. It covers everything from a basic understanding of Redis data types to advanced aspects of Redis high availability, clustering, administration, and troubleshooting. This book will be your great companion to master all aspects of Redis. The book starts off by installing and configuring Redis for you to get started with ease. Moving on, all the data types and features of Redis are introduced in detail. Next, you will learn how to develop applications with Redis in Java, Python, and the Spring Boot web framework. You will also learn replication tasks, which will help you to troubleshoot replication issues. Furthermore, you will learn the steps that need to be undertaken to ensure high availability on your cluster and during production deployment. Toward the end of the book, you will learn the topmost tasks that will help you to troubleshoot your ecosystem efficiently, along with extending Redis by using different modules. Style and approach This book is a rich collection of recipes that will come in handy when you are working with Redis. It addresses your common and not-so-common pain points, so this is a book of Redis that you must have on the shelf.

Your one stop guide to automating infrastructure security using DevOps and DevSecOps Key Features * Secure and automate techniques to protect web, mobile or cloud services * Automate secure code inspection in C++, Java, Python, and JavaScript * Integrate security testing with automation frameworks like fuzz, BDD, Selenium and Robot Framework Book Description Security automation is the automatic handling of software security assessments tasks. This book helps you to build your security automation framework to scan for vulnerabilities without human intervention. This book will teach you to adopt security automation techniques to continuously improve your entire software development and security testing. You will learn to use open source tools and techniques to integrate security testing tools directly into your CI/CD framework. With this book, you will see how to implement security inspection at every layer, such as secure code inspection, fuzz testing, Rest API, privacy, infrastructure security, and web UI testing. With the help of practical examples, this book will teach you to implement the combination of automation and Security in DevOps. You will learn about the integration of security testing results for an overall security status for projects. By the end of this book, you will be confident implementing automation security in all layers of your software development stages and will be able to build your own in-house security automation platform throughout your mobile and cloud releases. What you will learn * Automate secure code inspection with open source tools and effective secure code scanning suggestions * Apply security testing tools and automation frameworks to identify security vulnerabilities in web, mobile and cloud services * Integrate security testing tools such as OWASP ZAP, NMAP, SSLyze, SQLMap, and OpenSCAP * Implement automation testing techniques with Selenium, JMeter, Robot Framework, Gauntlt, BDD, DDT, and Python unittest * Execute security testing of a Rest API Implement web application security with open source tools and script templates for CI/CD integration * Integrate various types of security testing tool results from a single project into one dashboard Who this book is for The book is for software developers, architects, testers and QA engineers who are looking to leverage automated security testing techniques.

Create a real-world application in Go and explore various frameworks and methodologies for full-stack development Key Features * Organize your isomorphic codebase to enhance the maintainability of your application * Build web APIs and middleware in the Go language by making use of the popular Gin framework * Implement real-time web application functionality with WebSockets Book Description The Go programming language has been rapidly adopted by developers for building web applications. With its impressive performance and ease of development, Go enjoys the support of a wide variety of open source frameworks, for building scalable and high-performant web services and apps. Hands-On Full Stack Development with Go is a comprehensive guide that covers all aspects of full stack development with Go. This clearly written, example-rich book begins with a practical exposure to Go development and moves on to build a frontend with the popular React framework. From there, you will build RESTful web APIs utilizing the Gin framework. After that, we will dive deeper into important software backend concepts, such as connecting to the database via an ORM, designing routes for your services, securing your services, and even charging credit cards via the popular Stripe API. We will also cover how to test, and benchmark your applications efficiently in a production environment. In the concluding chapters, we will cover isomorphic developments in pure Go by learning about GopherJS. As you progress through the book, you'll gradually build a musical instrument online store application from scratch. By the end of the book, you will be confident in taking on full stack web applications in Go. What you will learn * Understand Go programming by building a real-world application * Learn the React framework to develop a frontend for your application * Understand isomorphic web development utilizing the GopherJS framework * Explore methods to write RESTful web APIs in Go using the Gin framework * Learn practical topics such as ORM layers, secure communications, and Stripe's API * Learn methods to benchmark and test web APIs in Go Who this book is for Hands-On Full Stack Development with Go will appeal to developers who are looking to start building amazing full stack web applications in Go. Basic knowhow of Go language and JavaScript is expected. The book targets web developers who are looking to move to the Go language.