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.

A pragmatic companion guide to your Agile journey About This Book ? Make your team Agile by implementing industry-standard Agile techniques ? Assess scope, scale up efficiently ? Create the correct roles and identify the right candidates for your team ? Finish your projects faster and stay ahead of the curve Who This Book Is For If you’re a software developer or a project manager with little to no experience of Agile, but you want to efficiently implement it, this is the book for you. What You Will Learn ? Create a solid foundation that gives your team an Agile jumpstart ? Understand how to select and evolve practices to increase your team’s agility ? Use experiments to accelerate your team’s understanding ? Fine-tune your approach by incorporating aspects of Lean and Lean Startup ? Know how to foster an environment of continuous improvement and learning that will become self-sustaining In Detail This book will help you overcome the common challenges you’ll face when transforming your working practices from waterfall to Agile. Each chapter builds on the last, starting with easy-to-grasp ways to get going with Agile. Next you’ll see how to choose the right Agile framework for your organization. Moving on, you’ll implement systematic product delivery and measure and report progress with visualization. Then you’ll learn how to create high performing teams, develop people in Agile, manage in Agile, and perform distributed Agile and collaborative governance. At the end of the book, you’ll discover how Agile will help your company progressively deliver software to customers, increase customer satisfaction, and improve the level of efficiency in software development teams. Style and approach Think of this book like a manual, rather than a theoretical textbook. It’s packed full of visual ways to understand Agile, helpful tips to get you set up quickly, tried and tested solutions when challenges arise, and heaps of support to get the day-to-day tasks in Agile done. You’ll want to keep a copy on your desk, right next to your coffee cup.

Discover new opportunities to empower your private cloud by making the most of the OpenStack universe About This Book ? This practical guide teaches you how to extend the core functionalities of OpenStack ? Discover OpenStack's flexibility by writing custom applications and network plugins ? Deploy a containerized environment in OpenStack through a hands-on and example-driven approach Who This Book Is For This book is for system administrators, cloud architects, and developers who have experience working with OpenStack and are ready to step up and extend its functionalities. A good knowledge of basic OpenStack components is required. In addition, familiarity with Linux boxes and a good understanding of network and virtualization jargon is required. What You Will Learn ? Explore new incubated projects in the OpenStack ecosystem and see how they work ? Architect your OpenStack private cloud with extended features of the latest versions ? Consolidate OpenStack authentication in your large infrastructure to avoid complexity ? Find out how to expand your computing power in OpenStack on a large scale ? Reduce your OpenStack storage cost management by taking advantage of external tools ? Provide easy, on-demand, cloud-ready applications to developers using OpenStack in no time ? Enter the big data world and find out how to launch elastic jobs easily in OpenStack ? Boost your extended OpenStack private cloud performance through real-world scenarios In Detail OpenStack is a very popular cloud computing platform that has enabled several organizations during the last few years to successfully implement their Infrastructure as a Service (IaaS) platforms. This book will guide you through new features of the latest OpenStack releases and how to bring them into production straightaway in an agile way. It starts by showing you how to expand your current OpenStack setup and how to approach your next OpenStack Data Center generation deployment. You will discover how to extend your storage and network capacity and also take advantage of containerization technology such as Docker and Kubernetes in OpenStack. Additionally, you'll explore the power of big data as a Service terminology implemented in OpenStack by integrating the Sahara project. This book will teach you how to build Hadoop clusters and launch jobs in a very simple way. Then you'll automate and deploy applications on top of OpenStack. You will discover how to write your own plugin in the Murano project. The final part of the book will go through best practices for security such as identity, access management, and authentication exposed by Keystone in OpenStack. By the end of this book, you will be ready to extend and customize your private cloud based on your requirements. Style and approach This guide is filled with practical scenarios on how to extend and enhance OpenStack's functionality. We will be covering various installation and configuration platforms along with a focus on plugins and extending OpenStack's core functionalities.

A practical guide filled with case studies and easy solutions to solve the most common user experience issues About This Book ? Understand and fix the pain points of a bad UX design to ensure greater customer satisfaction. ? Correct UX issues at various stages of a UX Design with the help of different methodologies for fixing bad UXs ? See best practices and established principles in UX with case studies illustrating these practices and principles Who This Book Is For This book is for anyone confronted with a poorly designed UX. It is ideal for UX professionals who want to solve problems with existing UX designs, and UX designers who want to enhance their designs or analyze and rectify where they went wrong. What You Will Learn ? Learn about ROI and metrics in UX ? Understand the importance of getting stakeholders involved ? Learn through real cases how to fix bad UX ? Identify and fix UX issues using different methodologies ? Learn how to turn insights and finding into practical UX solutions ? Learn to validate, test and measure the UX solutions implemented ? Learn about UX refactoring In Detail Have your web applications been experiencing more hits and less conversions? Are bad designs consuming your time and money? This book is the answer to these problems. With intuitive case studies, you’ll learn to simplify, fix, and enhance some common, real-world application designs. You’ll look at the common issues of simplicity, navigation, appearance, maintenance, and many more. The challenge that most UX designers face is to ensure that the UX is user-friendly. In this book, we address this with individual case studies starting with some common UX applications and then move on to complex applications. Each case study will help you understand the issues faced by a bad UX and teach you to break it down and fix these problems. As we progress, you’ll learn about the information architecture, usability testing, iteration, UX refactoring, and many other related features with the help of various case studies. You’ll also learn some interesting UX design tools with the projects covered in the book. By the end of the book, you’ll be armed with the knowledge to fix bad UX designs and to ensure great customer satisfaction for your applications. Style and approach This book takes a practical approach, with case studies, best practices, and practical solutions to bad design

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.

A tutorial leading the aspiring Go developer to full mastery of Golang's distributed features. About This Book ? This book provides enough concurrency theory to give you a contextual understanding of Go concurrency ? It gives weight to synchronous and asynchronous data streams in Golang web applications ? It makes Goroutines and Channels completely familiar and natural to Go developers Who This Book Is For This book is for developers who are familiar with the Golang syntax and have a good idea of how basic Go development works. It would be advantageous if you have been through a web application product cycle, although it’s not necessary. What You Will Learn ? Gain proficiency with concurrency and parallelism in Go ? Learn how to test your application using Go's standard library ? Learn industry best practices with technologies such as REST, OpenAPI, Docker, and so on ? Design and build a distributed search engine ? Learn strategies on how to design a system for web scale In Detail Distributed Computing with Go gives developers with a good idea how basic Go development works the tools to fulfill the true potential of Golang development in a world of concurrent web and cloud applications. Nikhil starts out by setting up a professional Go development environment. Then you’ll learn the basic concepts and practices of Golang concurrent and parallel development. You’ll find out in the new few chapters how to balance resources and data with REST and standard web approaches while keeping concurrency in mind. Most Go applications these days will run in a data center or on the cloud, which is a condition upon which the next chapter depends. There, you’ll expand your skills considerably by writing a distributed document indexing system during the next two chapters. This system has to balance a large corpus of documents with considerable analytical demands. Another use case is the way in which a web application written in Go can be consciously redesigned to take distributed features into account. The chapter is rather interesting for Go developers who have to migrate existing Go applications to computationally and memory-intensive environments. The final chapter relates to the rather onerous task of testing parallel and distributed applications, something that is not usually taught in standard computer science curricula. Style and approach Distributed Computing with Go takes you through a series of carefully graded tutorials, building ever more sophisticated applications.

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 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.

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

Develop rich and scalable web applications with Node.js, Express.js, and MongoDB About This Book ? Learn the advanced features of Aurelia to build responsive web applications ? Write clean, modular, and testable code that will be easy to maintain and evolve ? Harness the power of JavaScript on the client and server side to build full-stack applications Who This Book Is For Hands-On Full Stack Web Development with Aurelia is for you if you are a web or full-stack JavaScript developer who has experience with traditional stacks such as LAMP, MEAN, or MERN and wish to explore the power of Aurelia and new stack with modern web technologies. What You Will Learn ? Employ best practices and modern approaches to create frontend applications ? Learn about modern CSS preprocessors and improve the readability of your application ? Use the Aurelia framework to create navigable web applications ? Write your own tests, making your application secure and fault-tolerant ? Create solid RESTful APIs using the microservice architecture ? Understand the NoSQL paradigm and get the best performance from your database ? Integrate third-party libraries such as Gmail for Single Sign On ? Write UI testing scripts and integration tests to build extensible apps In Detail Hands-On Full Stack Web Development with Aurelia begins with a review of basic JavaScript concepts and the structure of an Aurelia application generated with the Aurelia-CLI tool. You will learn how to create interesting and intuitive application using the Aurelia-Materialize plugin, which implements the material design approach. Once you fully configure a FIFA World Cup 2018 app, you'll start creating the initial components through TDD practices and then develop backend services to process and store all the user data. This book lets you explore the NoSQL model and implement it using one of the most popular NoSQL databases, MongoDB, with some exciting libraries to make the experience effortless. You'll also be able to add some advanced behavior to your components, from managing the lifecycle properly to using dynamic binding, field validations, and the custom service layer. You will integrate your application with Google OAuth Service and learn best practices to secure your applications. Furthermore, you'll write UI Testing scripts to create high-quality Aurelia Apps and explore the most used tools to run end-to-end tests. In the concluding chapters, you'll be able to deploy your application to the Cloud and Docker containers. By the end of this book, you will have learned how to create rich applications using best practices and modern approaches. Style and approach This is a comprehensive example-based book that guides you to create highly scalable applications using the new MEAN Stack.

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

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

Get a solid understanding of Java fundamentals to master programming through a series of practical steps About This Book ? Enjoy your first step into the world of programming ? Understand what a language is and use its features to build applications ? Learn about a wide variety of programming applications Who This Book Is For Introduction to Programming is for anybody who wants to learn programming. All you’ll need is a computer, internet connection, and a cup of coffee. What You Will Learn ? Understand what Java is ? Install Java and learn how to run it ? Write and execute a Java program ? Write and execute the test for your program ? Install components and confgure your development environment ? Learn and use Java language fundamentals ? Learn object-oriented design principles ? Master the frequently used Java constructs In Detail Have you ever thought about making your computer do what you want it to do? Do you want to learn to program, but just don't know where to start? Instead of guiding you in the right direction, have other learning resources got you confused with over-explanations? Don't worry. Look no further. Introduction to Programming is here to help. Written by an industry expert who understands the challenges faced by those from a non-programming background, this book takes a gentle, hand-holding approach to introducing you to the world of programming. Beginning with an introduction to what programming is, you'll go on to learn about languages, their syntax, and development environments. With plenty of examples for you to code alongside reading, the book's practical approach will help you to grasp everything it has to offer. More importantly, you'll understand several aspects of application development. As a result, you'll have your very own application running by the end of the book. To help you comprehensively understand Java programming, there are exercises at the end of each chapter to keep things interesting and encourage you to add your own personal touch to the code and, ultimately, your application. Style and approach This step-by-step guide will familiarize you with programming using some practical examples.

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.

Solve real-world data problems with R and machine learning Key Features * Third edition of the bestselling, widely acclaimed R machine learning book, updated and improved for R 3.5 and beyond * Harness the power of R to build flexible, effective, and transparent machine learning models * Learn quickly with a clear, hands-on guide by experienced machine learning teacher and practitioner, Brett Lantz Book Description Machine learning, at its core, is concerned with transforming data into actionable knowledge. R offers a powerful set of machine learning methods to quickly and easily gain insight from your data. Machine Learning with R, Third Edition provides a hands-on, readable guide to applying machine learning to real-world problems. Whether you are an experienced R user or new to the language, Brett Lantz teaches you everything you need to uncover key insights, make new predictions, and visualize your findings. This new 3rd edition updates the classic R data science book with newer and better libraries, advice on ethical and bias issues in machine learning, and an introduction to deep learning. Find powerful new insights in your data; discover machine learning with R. What you will learn * Discover the origins of machine learning and how exactly a computer learns by example * Prepare your data for machine learning work with the R programming language * Classify important outcomes using nearest neighbor and Bayesian methods * Predict future events using decision trees, rules, and support vector machines * Forecast numeric data and estimate financial values using regression methods * Model complex processes with artificial neural networks — the basis of deep learning * Avoid bias in machine learning models * Evaluate your models and improve their performance * Connect R to SQL databases and emerging big data technologies such as Spark, H2O, and TensorFlow Who this book is for Data scientists, students, and other practitioners who want a clear, accessible guide to machine learning with R.

Implement defensive techniques in your ecosystem successfully with Python Key Features * Identify and expose vulnerabilities in your infrastructure with Python * Learn custom exploit development . * Make robust and powerful cybersecurity tools with Python Book Description With the current technological and infrastructural shift, penetration testing is no longer a process-oriented activity. Modern-day penetration testing demands lots of automation and innovation; the only language that dominates all its peers is Python. Given the huge number of tools written in Python, and its popularity in the penetration testing space, this language has always been the first choice for penetration testers. Hands-On Penetration Testing with Python walks you through advanced Python programming constructs. Once you are familiar with the core concepts, you’ll explore the advanced uses of Python in the domain of penetration testing and optimization. You’ll then move on to understanding how Python, data science, and the cybersecurity ecosystem communicate with one another. In the concluding chapters, you’ll study exploit development, reverse engineering, and cybersecurity use cases that can be automated with Python. By the end of this book, you’ll have acquired adequate skills to leverage Python as a helpful tool to pentest and secure infrastructure, while also creating your own custom exploits. What you will learn * Get to grips with Custom vulnerability scanner development * Familiarize yourself with web application scanning automation and exploit development * Walk through day-to-day cybersecurity scenarios that can be automated with Python * Discover enterprise-or organization-specific use cases and threat-hunting automation * Understand reverse engineering, fuzzing, buffer overflows , key-logger development, and exploit development for buffer overflows. * Understand web scraping in Python and use it for processing web responses * Explore Security Operations Centre (SOC) use cases * Get to understand Data Science, Python, and cybersecurity all under one hood Who this book is for If you are a security consultant , developer or a cyber security enthusiast with little or no knowledge of Python and want in-depth insight into how the pen-testing ecosystem and python combine to create offensive tools , exploits , automate cyber security use-cases and much more then this book is for you. Hands-On Penetration Testing with Python guides you through the advanced uses of Python for cybersecurity and pen-testing, helping you to better understand security loopholes within your infrastructure .