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

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.

Build effective regression models in R to extract valuable insights from real data About This Book ? Implement different regression analysis techniques to solve common problems in data science - from data exploration to dealing with missing values ? From Simple Linear Regression to Logistic Regression - this book covers all regression techniques and their implementation in R ? A complete guide to building effective regression models in R and interpreting results from them to make valuable predictions Who This Book Is For This book is intended for budding data scientists and data analysts who want to implement regression analysis techniques using R. If you are interested in statistics, data science, machine learning and wants to get an easy introduction to the topic, then this book is what you need! Basic understanding of statistics and math will help you to get the most out of the book. Some programming experience with R will also be helpful What You Will Learn ? Get started with the journey of data science using Simple linear regression ? Deal with interaction, collinearity and other problems using multiple linear regression ? Understand diagnostics and what to do if the assumptions fail with proper analysis ? Load your dataset, treat missing values, and plot relationships with exploratory data analysis ? Develop a perfect model keeping overfitting, under-fitting, and cross-validation into consideration ? Deal with classification problems by applying Logistic regression ? Explore other regression techniques – Decision trees, Bagging, and Boosting techniques ? Learn by getting it all in action with the help of a real world case study. In Detail Regression analysis is a statistical process which enables prediction of relationships between variables. The predictions are based on the casual effect of one variable upon another. Regression techniques for modeling and analyzing are employed on large set of data in order to reveal hidden relationship among the variables. This book will give you a rundown explaining what regression analysis is, explaining you the process from scratch. The first few chapters give an understanding of what the different types of learning are – supervised and unsupervised, how these learnings differ from each other. We then move to covering the supervised learning in details covering the various aspects of regression analysis. The outline of chapters are arranged in a way that gives a feel of all the steps covered in a data science process – loading the training dataset, handling missing values, EDA on the dataset, transformations and feature engineering, model building, assessing the model fitting and performance, and finally making predictions on unseen datasets. Each chapter starts with explaining the theoretical concepts and once the reader gets comfortable with the theory, we move to the practical examples to support the understanding. The practical examples are illustrated using R code including the different packages in R such as R Stats, Caret and so on. Each chapter is a mix of theory and practical examples. By the end of this book you will know all the concepts and pain-points related to regression analysis, and you will be able to implement your learning in your projects. Style and approach An easy-to-follow step by step guide which will help you get to grips with real world application of Regression Analysis with R

Master the capabilities of PostgreSQL 10 to efficiently manage and maintain your database About This Book ? Your one-stop guide to mastering advanced concepts in PostgreSQL 10 with ease ? Master query optimization, replication, and high availability with PostgreSQL ? Extend the functionalities of your PostgreSQL instance to suit your organizational needs with minimal effort Who This Book Is For If you are a PostgreSQL data architect or an administrator and want to understand how to implement advanced functionalities and master complex administrative tasks with PostgreSQL 10, then this book is perfect for you. Prior experience of administrating a PostgreSQL database and a working knowledge of SQL are required to make the best use of this book. What You Will Learn ? Get to grips with the advanced features of PostgreSQL 10 and handle advanced SQL ? Make use of the indexing features in PostgreSQL and fine-tune the performance of your queries ? Work with stored procedures and manage backup and recovery ? Master replication and failover techniques ? Troubleshoot your PostgreSQL instance for solutions to common and not-so-common problems ? Learn how to migrate your database from MySQL and Oracle to PostgreSQL without any hassle In Detail PostgreSQL is an open source database used for handling large datasets (big data) and as a JSON document database. This book highlights the newly introduced features in PostgreSQL 10, and shows you how you can build better PostgreSQL applications, and administer your PostgreSQL database more efficiently. We begin by explaining advanced database design concepts in PostgreSQL 10, along with indexing and query optimization. You will also see how to work with event triggers and perform concurrent transactions and table partitioning, along with exploring SQL and server tuning. We will walk you through implementing advanced administrative tasks such as server maintenance and monitoring, replication, recovery, high availability, and much more. You will understand common and not-so-common troubleshooting problems and how you can overcome them. By the end of this book, you will have an expert-level command of advanced database functionalities and will be able to implement advanced administrative tasks with PostgreSQL 10. Style and approach This mastering-level guide delves into the advanced functionalities of PostgreSQL 10

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.

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.

Join the virtual reality revolution by creating immersive 3D games and applications with Cardboard VR, Gear VR, OculusVR, and HTC Vive About This Book ? Develop robust, immersive VR experiences that are easy on the eye. ? Code 3D games and applications using Unity 3D game engine. ? Learn the basic principles of virtual reality applications Who This Book Is For If you are a game developer and a VR enthusiast now looking to get stuck into the VR app development process by creating VR apps for different platforms, then this is the book for you. Familiarity with the Unity game engine and the C# language is key to getting the most from this book. What You Will Learn ? Use Unity assets to create object simulation. ? Implement simple touch controls in your application. ? Apply artificial intelligence to achieve player and character interaction. ? Add *s for movement, tracking, grasping, and spawning. ? Create animated walkthroughs, use 360-degree media, and build engaging VR experiences. ? Deploy your games on multiple VR platforms. In Detail Are you new to virtual reality? Do you want to create exciting interactive VR applications? There's no need to be daunted by the thought of creating interactive VR applications, it's much easier than you think with this hands-on, project-based guide that will take you through VR development essentials for desktop and mobile-based games and applications. Explore the three top platforms—Cardboard VR, Gear VR, and OculusVR —to design immersive experiences from scratch. You’ll start by understanding the science-fiction roots of virtual reality and then build your first VR experience using Cardboard VR. You'll then delve into user interactions in virtual space for the Google Cardboard then move on to creating a virtual gallery with Gear VR. Then you will learn all about virtual movements, state machines, and spawning while you shoot zombies in the Oculus Rift headset. Next, you'll construct a Carnival Midway, complete with two common games to entertain players. Along the way, you will explore the best practices for VR development, review game design tips, discuss methods for combating motion sickness and identify alternate uses for VR applications Style and approach A project-based guide with every project built across chapters.

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.

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

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.

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.

Your one step guide to learn all about AWS networking. About This Book ? Master your networking skills on Public Cloud. ? Gain hands-on experience of using Amazon VPC, Elastic Load Balancing, Direct Connect and other AWS products. ? Implement troubleshooting skills and best practices for security on AWS network. Who This Book Is For This book is targeted towards cloud architects, cloud solution providers, or any stakeholders dealing with networking on AWS Cloud. A prior idea of Amazon Web Services will be an added advantage. What You Will Learn ? Overview of all networking services available in AWS. ? Gain Work with load balance application across different regions. ? Learn auto scale instance based on the increase and decrease of the traffic. ? Deploy application in highly available and fault tolerant manner. ? Configure Route 53 for a web application. ? Troubleshooting tips and best practices at the end In Detail Amazon Web Services (AWS) dominates the public cloud market by a huge margin and it continues to be the first choice for many organizations. Networking has been an area of focus for all the leading cloud service providers. AWS has a suite of network-related products that help to perform network-related task in AWS. This book initially covers the basics of networking in AWS. Then we use AWS VPC to create an isolated virtual cloud for performing network-related tasks. We then provide an overview of AWS Direct Connect after taking a deep dive into scalability and load balancing using Auto scaling feature, Elastic Load Balancing, and Amazon Route S3. Toward the end of the book, we cover some troubleshooting tips and security best practices for your network. By the end of this book, you will have hands-on experience of working with network tasks on AWS. Style and approach A step by step practical guide that helps you use all networking services available in AWS effectively.

A perfect guide to speed up the predicting power of machine learning algorithms About This Book ? Design, discover, and create dynamic, efficient features for your machine learning application ? Understand your data in-depth and derive astonishing data insights with the help of this Guide ? Grasp powerful feature-engineering techniques and build machine learning systems Who This Book Is For If you are a data science professional or a machine learning engineer looking to strengthen your predictive analytics model, then this book is a perfect guide for you. Some basic understanding of the machine learning concepts and Python *ing would be enough to get started with this book. What You Will Learn ? Identify and leverage different feature types ? Clean features in data to improve predictive power ? Understand why and how to perform feature selection, and model error analysis ? Leverage domain knowledge to construct new features ? Deliver features based on mathematical insights ? Use machine-learning algorithms to construct features ? Master feature engineering and optimization ? Harness feature engineering for real world applications through a structured case study In Detail Feature engineering is the most important step in creating powerful machine learning systems. This book will take you through the entire feature-engineering journey to make your machine learning much more systematic and effective. You will start with understanding your data—often the success of your ML models depends on how you leverage different feature types, such as continuous, categorical, and more, You will learn when to include a feature, when to omit it, and why, all by understanding error analysis and the acceptability of your models. You will learn to convert a problem statement into useful new features. You will learn to deliver features driven by business needs as well as mathematical insights. You'll also learn how to use machine learning on your machines, automatically learning amazing features for your data. By the end of the book, you will become proficient in Feature Selection, Feature Learning, and Feature Optimization. Style and approach This step-by-step guide with use cases, examples, and illustrations will help you master the concepts of feature engineering. Along with explaining the fundamentals, the book will also introduce you to slightly advanced concepts later on and will help you implement these techniques in the real world.

Learn how to model and train advanced neural networks to implement a variety of Computer Vision tasks About This Book ? Train different kinds of deep learning model from scratch to solve specific problems in Computer Vision ? Combine the power of Python, Keras, and TensorFlow to build deep learning models for object detection, image classification, similarity learning, image captioning, and more ? Includes tips on optimizing and improving the performance of your models under various constraints Who This Book Is For This book is targeted at data scientists and Computer Vision practitioners who wish to apply the concepts of Deep Learning to overcome any problem related to Computer Vision. A basic knowledge of programming in Python—and some understanding of machine learning concepts—is required to get the best out of this book. What You Will Learn ? Set up an environment for deep learning with Python, TensorFlow, and Keras ? Define and train a model for image and video classification ? Use features from a pre-trained Convolutional Neural Network model for image retrieval ? Understand and implement object detection using the real-world Pedestrian Detection scenario ? Learn about various problems in image captioning and how to overcome them by training images and text together ? Implement similarity matching and train a model for face recognition ? Understand the concept of generative models and use them for image generation ? Deploy your deep learning models and optimize them for high performance In Detail Deep learning has shown its power in several application areas of Artificial Intelligence, especially in Computer Vision. Computer Vision is the science of understanding and manipulating images, and finds enormous applications in the areas of robotics, automation, and so on. This book will also show you, with practical examples, how to develop Computer Vision applications by leveraging the power of deep learning. In this book, you will learn different techniques related to object classification, object detection, image segmentation, captioning, image generation, face analysis, and more. You will also explore their applications using popular Python libraries such as TensorFlow and Keras. This book will help you master state-of-the-art, deep learning algorithms and their implementation. Style and approach This book will teach advanced techniques for Computer Vision, applying the deep learning model in reference to various datasets.

Get up and running with all the new features of ECMAScript and explore new ways of coding with JavaScript. About This Book ? Grasp the latest features of ECMAScript and the best way to use it in production code ? Learn newly added native APIs to JS Engine and perform tasks efficiently with a cleaner code base ? Understand the more complex sides of JavaScript such as the inheritance model, low-level memory management, multithreaded environments, and web workers Who This Book Is For This book is for web developers who have some basic programming knowledge and want to learn to write cleaner code with the power of ECMAScript. What You Will Learn ? Implement methods associated with objects as per the latest ECMAScript specification ? Make use of the latest features of ECMAScript ? Make use of many new APIs in HTML5 and modern JavaScript implementation ? Use SharedArrayBuffers for superfast concurrent and parallel programming ? Perform asynchronous programming with JavaScript ? Implement the best ways and practices to perform modular programming in JavaScript In Detail Learn ECMAScript explores implementation of the latest ECMAScript features to add to your developer toolbox, helping you to progress to an advanced level. Learn to add 1 to a variable andsafely access shared memory data within multiple threads to avoid race conditions. You’ll start the book by building on your existing knowledge of JavaScript, covering performing arithmetic operations, using arrow functions and dealing with closures. Next, you will grasp the most commonly used ECMAScript skills such as reflection, proxies, and classes. Furthermore, you’ll learn modularizing the JS code base, implementing JS on the web and how the modern HTML5 + JS APIs provide power to developers on the web. Finally, you will learn the deeper parts of the language, which include making JavaScript multithreaded with dedicated and shared web workers, memory management, shared memory, and atomics. It doesn’t end here; this book is 100% compatible with ES.Next. By the end of this book, you'll have fully mastered all the features of ECMAScript! Style and approach The level goes gradually from basic to advanced so that the reader can adapt at every point and level up their skills at the same time. The chapters are carefully arranged in a manner that makes every concept easy to learn and deploy right away in your code.

Develop and run efficient R *s and predictive models for SQL Server 2017 About This Book ? Learn how you can combine the power of R and SQL Server 2017 to build efficient, cost-effective data science solutions ? Leverage the capabilities of R Services to perform advanced analytics—from data exploration to predictive modeling ? A quick primer with practical examples to help you get up- and- running with SQL Server 2017 Machine Learning Services with R, as part of database solutions with continuous integration / continuous delivery. Who This Book Is For This book is for data analysts, data scientists, and database administrators with some or no experience in R but who are eager to easily deliver practical data science solutions in their day-to-day work (or future projects) using SQL Server. What You Will Learn ? Get an overview of SQL Server 2017 Machine Learning Services with R ? Manage SQL Server Machine Learning Services from installation to configuration and maintenance ? Handle and operationalize R code ? Explore RevoScaleR R algorithms and create predictive models ? Deploy, manage, and monitor database solutions with R ? Extend R with SQL Server 2017 features ? Explore the power of R for database administrators In Detail R Services was one of the most anticipated features in SQL Server 2016, improved significantly and rebranded as SQL Server 2017 Machine Learning Services. Prior to SQL Server 2016, many developers and data scientists were already using R to connect to SQL Server in siloed environments that left a lot to be desired, in order to do additional data analysis, superseding SSAS Data Mining or additional CLR programming functions. With R integrated within SQL Server 2017, these developers and data scientists can now benefit from its integrated, effective, efficient, and more streamlined analytics environment. This book gives you foundational knowledge and insights to help you understand SQL Server 2017 Machine Learning Services with R. First and foremost, the book provides practical examples on how to implement, use, and understand SQL Server and R integration in corporate environments, and also provides explanations and underlying motivations. It covers installing Machine Learning Services;maintaining, deploying, and managing code;and monitoring your services. Delving more deeply into predictive modeling and the RevoScaleR package, this book also provides insights into operationalizing code and exploring and visualizing data. To complete the journey, this book covers the new features in SQL Server 2017 and how they are compatible with R, amplifying their combined power. Style and approach This fast-paced guide will help data scientists and DBAs implement all new data science projects using SQL Server 2017 Machine Learning Services.

Untangle your web scraping complexities and access web data with ease using Python *s About This Book ? Hands-on recipes for advancing your web scraping skills to expert level. ? One-Stop Solution Guide to address complex and challenging web scraping tasks using Python. ? Understand the web page structure and collect meaningful data from the website with ease Who This Book Is For This book is ideal for Python programmers, web administrators, security professionals or someone who wants to perform web analytics would find this book relevant and useful. Familiarity with Python and basic understanding of web scraping would be useful to take full advantage of this book. What You Will Learn ? Use a wide variety of tools to scrape any website and data—including BeautifulSoup, Scrapy, Selenium, and many more ? Master expression languages such as XPath, CSS, and regular expressions to extract web data ? Deal with scraping traps such as hidden form fields, throttling, pagination, and different status codes ? Build robust scraping pipelines with SQS and RabbitMQ ? Scrape assets such as images media and know what to do when Scraper fails to run ? Explore ETL techniques of build a customized crawler, parser, and convert structured and unstructured data from websites ? Deploy and run your scraper-as-aservice in AWS Elastic Container Service In Detail Python Web Scraping Cookbook is a solution-focused book that will teach you techniques to develop high-performance scrapers and deal with crawlers, sitemaps, forms automation, Ajax-based sites, caches, and more.You'll explore a number of real-world scenarios where every part of the development/product life cycle will be fully covered. You will not only develop the skills to design and develop reliable, performance data flows, but also deploy your codebase to an AWS. If you are involved in software engineering, product development, or data mining (or are interested in building data-driven products), you will find this book useful as each recipe has a clear purpose and objective. Right from extracting data from the websites to writing a sophisticated web crawler, the book's independent recipes will be a godsend on the job. This book covers Python libraries, requests, and BeautifulSoup. You will learn about crawling, web spidering, working with AJAX websites, paginated items, and more. You will also learn to tackle problems such as 403 errors, working with proxy, scraping images, LXML, and more. By the end of this book, you will be able to scrape websites more efficiently and to be able to deploy and operate your scraper in the cloud. Style and approach This book is a rich collection of recipes that will come in handy when you are scraping a website using Python. Addressing your common and not-so-common pain points while scraping website, this is a book that you must have on the shelf.

Design, build and test RESTful web services with the Django framework and Python About This Book ? Create efficient real-world RESTful web services with the latest Django framework ? Authenticate, secure, and integrate third-party packages efficiently in your Web Services ? Leverage the power of Python for faster Web Service development Who This Book Is For This book is for Python developers who want to create RESTful web services with Django; you need to have a basic working knowledge of Django but no previous experience with RESTful web services is required. What You Will Learn ? The best way to build a RESTful Web Service or API with Django and the Django REST Framework ? Develop complex RESTful APIs from scratch with Django and the Django REST Framework ? Work with either SQL or NoSQL data sources ? Design RESTful Web Services based on application requirements ? Use third-party packages and extensions to perform common tasks ? Create automated tests for RESTful web services ? Debug, test, and profile RESTful web services with Django and the Django REST Framework In Detail Django is a Python web framework that makes the web development process very easy. It reduces the amount of trivial code, which simplifies the creation of web applications and results in faster development. It is very powerful and a great choice for creating RESTful web services. If you are a Python developer and want to efficiently create RESTful web services with Django for your apps, then this is the right book for you. The book starts off by showing you how to install and configure the environment, required software, and tools to create RESTful web services with Django and the Django REST framework. We then move on to working with advanced serialization and migrations to interact with SQLite and non-SQL data sources. We will use the features included in the Django REST framework to improve our simple web service. Further, we will create API views to process diverse HTTP requests on objects, go through relationships and hyperlinked API management, and then discover the necessary steps to include security and permissions related to data models and APIs. We will also apply throttling rules and run tests to check that versioning works as expected. Next we will run automated tests to improve code coverage. By the end of the book, you will be able to build RESTful web services with Django." Style and approach The book takes a straightforward approach, giving you the techniques and best use cases to build great web services with Django and Python

Learn to build a high-performance functional prototype of a voting web application from scratch using Elixir and Phoenix About This Book ? Build a strong foundation in Functional-Programming techniques while learning to build compelling web applications ? Understand the Elixir Concurrency and parallelization model to build high-performing blazingly fast applications ? Learn to test, debug and deploy your web applications using Phoenix framework Who This Book Is For This book is for people with a basic knowledge of Elixir, who want to start building web applications. Prior experience with web technologies is assumed. What You Will Learn ? Learn Phoenix Framework fundamentals and v1.3's new application structure ? Build real-time applications with channels and presence ? Utilize GenServers and other OTP fundamentals to keep an application stable ? Track users as they sign in and out of chat with Phoenix’s built-in presence functionality ? Write your own database interaction code that is safe, bug-free, and easy to work with ? Explore testing and debugging methodologies to understand a real software development lifecycle for a Phoenix application ? Deploy and run your Phoenix application in production In Detail Phoenix is a modern web development framework that is used to build API’s and web applications. It is built on Elixir and runs on Erlang VM which makes it much faster than other options. With Elixir and Phoenix, you build your application the right way, ready to scale and ready for the increasing demands of real-time web applications. This book covers the basics of the Phoenix web framework, showing you how to build a community voting application, and is divided into three parts. In the first part, you will be introduced to Phoenix and Elixir and understand the core terminologies that are used to describe them. You will also learn to build controller pages, store and retrieve data, add users to your app pages and protect your database. In the second section you will be able to reinforce your knowledge of architecting real time applications in phoenix and not only debug these applications but also diagnose issues in them. In the third and final section you will have the complete understanding of deploying and running the phoenix application and should be comfortable to make your first application release By the end of this book, you'll have a strong grasp of all of the core fundamentals of the Phoenix framework, and will have built a full production-ready web application from scratch. Style and approach Covers the basics of the Phoenix web framework by building a complete real-time application and showing the new structure changes introduced in Phoenix v1.3

Manage on-premises and cloud IT assets from one console About This Book ? Empower yourself with practical recipes to collect and analyze operational insights on Windows and Linux servers in your on premises datacenters and in any public cloud environments such as Azure and AWS. ? Build capabilities through practical tasks and techniques to collect and analyze machine data ? Address business challenges and discover means to accommodate workloads and instances in a low cost manner Who This Book Is For This book is written for the IT professional and general reader who is interested in technology themes such as DevOps, Big Data Analytics, and digital transformation concepts. Azure and other cloud platform administrators, cloud professionals, and technology analysts who would like to solve everyday problems quickly and efficiently with hybrid management tools available in the Microsoft product ecosystem will derive much value from this book. Prior experience with OMS 2012 would be helpful. What You Will Learn ? Understand the important architectural considerations and strategies for OMS ? Use advanced search query commands and strategies to derive insights from indexed data ? Make use of alerting in OMS such as alert actions, and available options for the entire lifecycle of the alert ? Discover some practical tips for monitoring Azure container service containers and clusters using OMS ? Review and use the backup options available through the Azure backup service, as well as data recovery options available through Azure Site Recovery (ASR) ? Understand how to advance important DevOps concepts within your IT organization ? Learn how to manage configurations and automate process In Detail Microsoft Operations Management Suite Cookbook begins with an overview of how to hit the ground running with OMS insights and analytics. Next, you will learn to search and analyze data to retrieve actionable insights, review alert generation from the analyzed data, and use basic and advanced Log search queries in Azure Log Analytics. Following this, you will explore some other management solutions that provide functionality related to workload assessment, application dependency mapping, automation and configuration management, and security and compliance. You will also become well versed with the data protection and recovery functionalities of OMS Protection and Recovery, and learn how to use Azure Automation components and features in OMS. Finally you will learn how to evaluate key considerations for using the Security and Audit solution, and working with Security and Compliance in OMS. By the end of the book, you will be able to configure and utilize solution offerings in OMS, understand OMS workflows, how to unlock insights, integrate capabilities into new or existing workflows, manage configurations, and automate tasks and processes. Style and approach This is a recipe based guide where early chapters introduce the main concepts and key capabilities, and the later chapters delve into more advance concepts.

Develop and manage applications on the AWS and OpenStack platforms with this comprehensive learning guide. About This Book ? A step-by-step guide to help you develop applications on the hybrid cloud platform. ? Acquire an in-depth understanding of the OpenStack and AWS cloud platforms. ? Extensive source code examples for OpenStack and AWS applications. ? Easily troubleshoot OpenStack and AWS issues. ? Understand the best practices and security measures for the hybrid cloud platform. Who This Book Is For If you are an IT professional, developer, or a DevOps engineer looking to develop and manage your applications on the hybrid cloud platform, then this book is for you. Some prior knowledge of the public and private cloud will enhance your skills. Developers looking to build applications using AWS or OpenStack services will also benefit from this book. What You Will Learn ? Understand the hybrid cloud platform ? Explore the AWS and OpenStack cloud platforms in depth ? Develop AWS applications with source code examples ? Develop OpenStack applications with source code examples ? Troubleshoot OpenStack and AWS ? Learn hybrid cloud best practices ? Understand security measures on the hybrid cloud In Detail This book introduces you to the hybrid cloud platform, and focuses on the AWS public cloud and OpenStack private cloud platforms. It provides a deep dive into the AWS and OpenStack cloud platform services that are essential for developing hybrid cloud applications. You will learn to develop applications on AWS and OpenStack platforms with ease by leveraging various cloud services and taking advantage of PaaS. The book provides you with the ability to leverage the flexibility of choosing a cloud platform for migrating your existing resources to the cloud, as well as developing hybrid cloud applications that can migrate virtual machine instances from AWS to OpenStack and vice versa. You will also be able to build and test cloud applications without worrying about the system that your development environment supports. The book also provides an in-depth understanding of the best practices that are followed across the industry for developing cloud applications, as well as for adapting the hybrid cloud platform. Lastly, it also sheds light on various troubleshooting techniques for OpenStack and AWS cloud platform services that are consumed by hybrid cloud applications. By the end of this book, you will have a deep understanding of the hybrid cloud platform and will be able to develop robust, efficient, modular, scalable, and ?exible cloud applications. Style and approach This book follows a practical approach to become familiar with the AWS and OpenStack platform from a developer's perspective.