Gain comprehensive insight into WPF mechanics and capabilities. About This Book ? Gain a strong foundation in WPF features and patterns ? Leverage the MVVM pattern to build decoupled, maintainable apps ? Increase efficiency through Performance tuning and UI automation Who This Book Is For The book is intended for developers who are relatively new to WPF (Windows Presentation Foundation), or those who have been working with WPF for some time, but want to get a deeper understanding of its foundation and concepts to gain practical knowledge. Basic knowledge of C# and Visual Studio is assumed. What You Will Learn ? Understand the fundamentals of WPF ? Explore the major controls and manage element layout ? Implement data binding ? Create custom elements that lead to a particular implementation path ? Customize controls, styles, and templates in XAML ? Leverage the MVVM pattern to maintain a clean and reusable structure in your code ? Master practical animations ? Integrate WCF services in a WPF application ? Implement WPFs support for debugging and asynchronous operations In Detail Windows Presentation Foundation (WPF) is Microsoft's development tool for building rich Windows client user experiences that incorporate UIs, media, and documents. With the updates in .NET 4.7, Visual Studio 2017, C# 7, and .NET Standard 2.0, WPF has taken giant strides and is now easier than ever for developers to use. If you want to get an in-depth view of WPF mechanics and capabilities, then this book is for you. The book begins by teaching you about the fundamentals of WPF and then quickly shows you the standard controls and the layout options. It teaches you about data bindings and how to utilize resources and the MVVM pattern to maintain a clean and reusable structure in your code. After this, you will explore the animation capabilities of WPF and see how they integrate with other mechanisms. Towards the end of the book, you will learn about WCF services and explore WPF's support for debugging and asynchronous operations. By the end of the book, you will have a deep understanding of WPF and will know how to build resilient applications. Style and approach This book takes a recipe-based approach to teaching you how to create fault-tolerant WPF applications.

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.

Highly available microservice-based web apps for Cloud with Java About This Book ? Take advantage of the simplicity of Spring to build a full-fledged application ? Let your applications run faster while generating smaller cloud service bills ? Integrate your application with various tools such as Docker and ElasticSearch and use specific tools in Azure and AWS Who This Book Is For Java developers who want to build secure, resilient, robust and scalable applications that are targeted for cloud based deployment, will find this book helpful. Some knowledge of Java, Spring, web programming and public cloud providers (AWS, Azure) should be sufficient to get you through the book. What You Will Learn ? See the benefits of the cloud environment when it comes to variability, provisioning, and tooling support ? Understand the architecture patterns and considerations when developing on the cloud ? Find out how to perform cloud-native techniques/patterns for request routing, RESTful service creation, Event Sourcing, and more ? Create Docker containers for microservices and set up continuous integration using Jenkins ? Monitor and troubleshoot an application deployed in the cloud environment ? Explore tools such as Docker and Kubernetes for containerization and the ELK stack for log aggregation and visualization ? Use AWS and Azure specific tools to design, develop, deploy, and manage applications ? Migrate from monolithic architectures to a cloud native deployment In Detail Businesses today are evolving so rapidly that they are resorting to the elasticity of the cloud to provide a platform to build and deploy their highly scalable applications. This means developers now are faced with the challenge of building build applications that are native to the cloud. For this, they need to be aware of the environment, tools, and resources they’re coding against. If you’re a Java developer who wants to build secure, resilient, robust, and scalable applications that are targeted for cloud-based deployment, this is the book for you. It will be your one stop guide to building cloud-native applications in Java Spring that are hosted in On-prem or cloud providers - AWS and Azure The book begins by explaining the driving factors for cloud adoption and shows you how cloud deployment is different from regular application deployment on a standard data centre. You will learn about design patterns specific to applications running in the cloud and find out how you can build a microservice in Java Spring using REST APIs You will then take a deep dive into the lifecycle of building, testing, and deploying applications with maximum automation to reduce the deployment cycle time. Gradually, you will move on to configuring the AWS and Azure platforms and working with their APIs to deploy your application. Finally, you’ll take a look at API design concerns and their best practices. You’ll also learn how to migrate an existing monolithic application into distributed cloud native applications. By the end, you will understand how to build and monitor a scalable, resilient, and robust cloud native application that is always available and fault tolerant. Style and approach Filled with examples, this book will build you an entire cloud-native application through its course and will stop at each point and explain in depth the functioning and design considerations that will make a robust, highly available application

Build fast, scalable, and high performing applications with Delphi About This Book ? Build efficient and concurrent applications in Delphi with focused examples ? Identify performance bottlenecks and apply the correct algorithm to increase the performance of applications. ? Delve into parallel programming and memory management to optimize your code Who This Book Is For This book is for Delphi developers who would like to build high performance applications with Delphi. Prior knowledge of Delphi is assumed. What You Will Learn ? Find performance bottlenecks and easily mitigate them ? Discover different approaches to fix algorithms ? Understand parallel programming and work with various tools included with Delphi ? Master the RTL for code optimization ? Explore memory managers and their implementation ? Leverage external libraries to write better performing programs In Detail Delphi is a cross-platform Integrated Development Environment (IDE) that supports rapid application development for Microsoft Windows, Apple Mac OS X, Google Android, iOS, and now Linux with RAD Studio 10.2. This book will be your guide to build efficient high performance applications with Delphi. The book begins by explaining how to find performance bottlenecks and apply the correct algorithm to fix them. It will teach you how to improve your algorithms before taking you through parallel programming. You’ll then explore various tools to build highly concurrent applications. After that, you’ll delve into improving the performance of your code and master cross-platform RTL improvements. Finally, we’ll go through memory management with Delphi and you’ll see how to leverage several external libraries to write better performing programs. By the end of the book, you’ll have the knowledge to create high performance applications with Delphi. Style and approach This book will take a step-by-step approach with focused examples to teach you how to increase the performance of applications.

Discover best practices and troubleshooting solutions when working on ROS About This Book ? Develop complex robotic applications using ROS to interface robot manipulators and mobile robots ? Gain insight into autonomous navigation in mobile robots and motion planning in robot manipulators ? Discover best practices and troubleshooting solutions Who This Book Is For If you are a robotics enthusiast or researcher who want to learn more about building robot applications using ROS, this book is for you. In order to learn from this book, you should have a basic knowledge of ROS, GNU/Linux, and C++ programming concepts. The book is also excellent for programmers who want to explore the advanced features of ROS. What You Will Learn ? Create a robot model with a seven-DOF robotic arm and a differential wheeled mobile robot ? Work with Gazebo and V-REP robotic simulator ? Implement autonomous navigation in differential drive robots using SLAM and AMCL packages ? Explore the ROS Pluginlib, ROS nodelets, and Gazebo plugins ? Interface I/O boards such as Arduino, robot sensors, and high-end actuators ? Simulate and motion plan an ABB and universal arm using ROS Industrial ? Explore the latest version of the ROS framework ? Work with the motion planning of a seven-DOF arm using MoveIt! In Detail In this day and age, robotics has been gaining a lot of traction in various industries where consistency and perfection matter. Automation is achieved via robotic applications and various platforms that support robotics. The Robot Operating System (ROS) is a modular software platform to develop generic robotic applications. This book focuses on the most stable release of ROS (Kinetic Kame), discusses advanced concepts, and effectively teaches you programming using ROS. We begin with aninformative overview of the ROS framework, which will give you a clear idea of how ROS works. During the course of this book, you’ll learn to build models of complex robots, and simulate and interface the robot using the ROS MoveIt! motion planning library and ROS navigation stacks. Learn to leverage several ROS packages to embrace your robot models. After covering robot manipulation and navigation, you’ll get to grips with the interfacing I/O boards, sensors, and actuators of ROS. Vision sensors are a key component of robots, and an entire chapter is dedicated to the vision sensor and image elaboration, its interface in ROS and programming. You’ll also understand the hardware interface and simulation of complex robots to ROS and ROS Industrial. At the end of this book, you’ll discover the best practices to follow when programming using ROS. Style and approach This is a simplified guide to help you learn and master advanced topics in ROS using hands-on examples.

A highly detailed guide to performing powerful attack vectors in many hands-on scenarios and defending significant security flaws in your company's infrastructure About This Book ? Advanced exploitation techniques to breach modern operating systems and complex network devices ? Learn about Docker breakouts, Active Directory delegation, and CRON jobs ? Practical use cases to deliver an intelligent endpoint-protected system Who This Book Is For If you are a system administrator, SOC analyst, penetration tester, or a network engineer and want to take your penetration testing skills and security knowledge to the next level, then this book is for you. Some prior experience with penetration testing tools and knowledge of Linux and Windows command-line syntax is beneficial. What You Will Learn ? Exposure to advanced infrastructure penetration testing techniques and methodologies ? Gain hands-on experience of penetration testing in Linux system vulnerabilities and memory exploitation ? Understand what it takes to break into enterprise networks ? Learn to secure the configuration management environment and continuous delivery pipeline ? Gain an understanding of how to exploit networks and IoT devices ? Discover real-world, post-exploitation techniques and countermeasures In Detail It has always been difficult to gain hands-on experience and a comprehensive understanding of advanced penetration testing techniques and vulnerability assessment and management. This book will be your one-stop solution to compromising complex network devices and modern operating systems. This book provides you with advanced penetration testing techniques that will help you exploit databases, web and application servers, switches or routers, Docker, VLAN, VoIP, and VPN. With this book, you will explore exploitation abilities such as offensive PowerShell tools and techniques, CI servers, database exploitation, Active Directory delegation, kernel exploits, cron jobs, VLAN hopping, and Docker breakouts. Moving on, this book will not only walk you through managing vulnerabilities, but will also teach you how to ensure endpoint protection. Toward the end of this book, you will also discover post-exploitation tips, tools, and methodologies to help your organization build an intelligent security system. By the end of this book, you will have mastered the skills and methodologies needed to breach infrastructures and provide complete endpoint protection for your system. Style and approach Your one-stop guide to mastering the skills and methodologies of breaching infrastructures and providing complete endpoint protection to your system.

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.

Leverage the WiFi chip to build exciting Quadcopters About This Book ? Learn to create a fully functional Drone with Arduino and ESP8266 and their modified versions of hardware. ? Enhance your drone's functionalities by implementing smart features. ? A project-based guide that will get you developing next-level drones to help you monitor a particular area with mobile-like devices. Who This Book Is For If you are a programmer or a DIY enthusiast and keen to create a fully functional drone with Arduino and ESP8266, then this book is for you. Basic skills in electronics and programming would be beneficial. This book is not for the beginners as it includes lots of ideas not detailed how you can do that. If you are a beginner, then you might get lost here. The prerequisites of the book include a good knowledge of Arduino, electronics, programming in C or C++ and lots of interest in creating things out of nothing. What You Will Learn ? Includes a number of projects that utilize different ESP8266 and Arduino capabilities, while interfacing with external hardware ? Covers electrical engineering and programming concepts, interfacing with the World through analog and digital sensors, communicating with a computer and other devices, and internet connectivity ? Control and fly your quadcopter, taking into account weather conditions ? Build a drone that can follow the user wherever he/she goes ? Build a mission-control drone and learn how to use it effectively ? Maintain your vehicle as much as possible and repair it whenever required In Detail With the use of drones, DIY projects have taken off. Programmers are rapidly moving from traditional application programming to developing exciting multi-utility projects. This book will teach you to build industry-level drones with Arduino and ESP8266 and their modified versions of hardware. With this book, you will explore techniques for leveraging the tiny WiFi chip to enhance your drone and control it over a mobile phone. This book will start with teaching you how to solve problems while building your own WiFi controlled Arduino based drone. You will also learn how to build a Quadcopter and a mission critical drone. Moving on you will learn how to build a prototype drone that will be given a mission to complete which it will do it itself. You will also learn to build various exciting projects such as gliding and racing drones. By the end of this book you will learn how to maintain and troubleshoot your drone. By the end of this book, you will have learned to build drones using ESP8266 and Arduino and leverage their functionalities to the fullest. Style and approach This is an easy-to-follow guide with illustrations and technical de*ions to help you assemble your vehicle.

Become an advanced practitioner with this progressive set of master classes on application-oriented machine learning About This Book ? Comprehensive coverage of key topics in machine learning with an emphasis on both the theoretical and practical aspects ? More than 15 open source Java tools in a wide range of techniques, with code and practical usage. ? More than 10 real-world case studies in machine learning highlighting techniques ranging from data ingestion up to analyzing the results of experiments, all preparing the user for the practical, real-world use of tools and data analysis. Who This Book Is For This book will appeal to anyone with a serious interest in topics in Data Science or those already working in related areas: ideally, intermediate-level data analysts and data scientists with experience in Java. Preferably, you will have experience with the fundamentals of machine learning and now have a desire to explore the area further, are up to grappling with the mathematical complexities of its algorithms, and you wish to learn the complete ins and outs of practical machine learning. What You Will Learn ? Master key Java machine learning libraries, and what kind of problem each can solve, with theory and practical guidance. ? Explore powerful techniques in each major category of machine learning such as classification, clustering, anomaly detection, graph modeling, and text mining. ? Apply machine learning to real-world data with methodologies, processes, applications, and analysis. ? Techniques and experiments developed around the latest specializations in machine learning, such as deep learning, stream data mining, and active and semi-supervised learning. ? Build high-performing, real-time, adaptive predictive models for batch- and stream-based big data learning using the latest tools and methodologies. ? Get a deeper understanding of technologies leading towards a more powerful AI applicable in various domains such as Security, Financial Crime, Internet of Things, social networking, and so on. In Detail Java is one of the main languages used by practicing data scientists; much of the Hadoop ecosystem is Java-based, and it is certainly the language that most production systems in Data Science are written in. If you know Java, Mastering Machine Learning with Java is your next step on the path to becoming an advanced practitioner in Data Science. This book aims to introduce you to an array of advanced techniques in machine learning, including classification, clustering, anomaly detection, stream learning, active learning, semi-supervised learning, probabilistic graph modeling, text mining, deep learning, and big data batch and stream machine learning. Accompanying each chapter are illustrative examples and real-world case studies that show how to apply the newly learned techniques using sound methodologies and the best Java-based tools available today. On completing this book, you will have an understanding of the tools and techniques for building powerful machine learning models to solve data science problems in just about any domain. Style and approach A practical guide to help you explore machine learning—and an array of Java-based tools and frameworks—with the help of practical examples and real-world use cases.

Build scalable, reliable, and cost-effective applications with a serverless architecture About This Book ? Design a real-world serverless application from scratch ? Learn about AWS Lambda function and how to use Lambda functions to glue other AWS Services ? Use the Java programming language and well-known design patterns. Although Java is used for the examples in this book, the concept is applicable across all languages ? Learn to migrate your JAX-RS application to AWS Lambda and API Gateway Who This Book Is For This book is for developers and software architects who are interested in designing on the back end. Since the book uses Java to teach concepts, knowledge of Java is required. What You Will Learn ? Learn to form microservices from bigger Softwares ? Orchestrate and scale microservices ? Design and set up the data flow between cloud services and custom business logic ? Get to grips with cloud provider’s APIs, limitations, and known issues ? Migrate existing Java applications to a serverless architecture ? Acquire deployment strategies ? Build a highly available and scalable data persistence layer ? Unravel cost optimization techniques In Detail Over the past years, all kind of companies from start-ups to giant enterprises started their move to public cloud providers in order to save their costs and reduce the operation effort needed to keep their shops open. Now it is even possible to craft a complex software system consisting of many independent micro-functions that will run only when they are needed without needing to maintain individual servers. The focus of this book is to design serverless architectures, and weigh the advantages and disadvantages of this approach, along with decision factors to consider. You will learn how to design a serverless application, get to know that key points of services that serverless applications are based on, and known issues and solutions. The book addresses key challenges such as how to slice out the core functionality of the software to be distributed in different cloud services and cloud functions. It covers basic and advanced usage of these services, testing and securing the serverless software, automating deployment, and more. By the end of the book, you will be equipped with knowledge of new tools and techniques to keep up with this evolution in the IT industry. Style and approach The book takes a pragmatic approach, showing you all the examples you need to build efficient serverless applications.

A practical guide to help you undertand the ability of Apache jMeter to load and performance test various server types in a more efficient way. About This Book ? Use jMeter to create and run tests to improve the performance of your webpages and applications ? Learn to build a test plan for your websites and analyze the results ? Unleash the power of various features and changes introduced in Apache jMeter 3.0 Who This Book Is For This book is for software professionals who want to understand and improve the performance of their applications with Apache jMeter. What You Will Learn ? See why performance testing is necessary and learn how to set up JMeter ? Record and test with JMeter ? Handle various form inputs in JMeter and parse results during testing ? Manage user sessions in web applications in the context of a JMeter test ? Monitor JMeter results in real time ? Perform distributed testing with JMeter ? Get acquainted with helpful tips and best practices for working with JMeter In Detail JMeter is a Java application designed to load and test performance for web application. JMeter extends to improve the functioning of various other static and dynamic resources. This book is a great starting point to learn about JMeter. It covers the new features introduced with JMeter 3 and enables you to dive deep into the new techniques needed for measuring your website performance. The book starts with the basics of performance testing and guides you through recording your first test scenario, before diving deeper into JMeter. You will also learn how to configure JMeter and browsers to help record test plans. Moving on, you will learn how to capture form submission in JMeter, dive into managing sessions with JMeter and see how to leverage some of the components provided by JMeter to handle web application HTTP sessions. You will also learn how JMeter can help monitor tests in real-time. Further, you will go in depth into distributed testing and see how to leverage the capabilities of JMeter to accomplish this. You will get acquainted with some tips and best practices with regard to performance testing. By the end of the book, you will have learned how to take full advantage of the real power behind Apache JMeter. Style and approach The book is a practical guide starting with introducing the readers to the importance of automated testing. It will then be a beginner’s journey from getting introduced to Apache jMeter to an in-detail discussion of more advanced features and possibilities with it.

Build Machine Learning models with a sound statistical understanding. About This Book ? Learn about the statistics behind powerful predictive models with p-value, ANOVA, and F- statistics. ? Implement statistical computations programmatically for supervised and unsupervised learning through K-means clustering. ? Master the statistical aspect of Machine Learning with the help of this example-rich guide to R and Python. Who This Book Is For This book is intended for developers with little to no background in statistics, who want to implement Machine Learning in their systems. Some programming knowledge in R or Python will be useful. What You Will Learn ? Understand the Statistical and Machine Learning fundamentals necessary to build models ? Understand the major differences and parallels between the statistical way and the Machine Learning way to solve problems ? Learn how to prepare data and feed models by using the appropriate Machine Learning algorithms from the more-than-adequate R and Python packages ? Analyze the results and tune the model appropriately to your own predictive goals ? Understand the concepts of required statistics for Machine Learning ? Introduce yourself to necessary fundamentals required for building supervised & unsupervised deep learning models ? Learn reinforcement learning and its application in the field of artificial intelligence domain In Detail Complex statistics in Machine Learning worry a lot of developers. Knowing statistics helps you build strong Machine Learning models that are optimized for a given problem statement. This book will teach you all it takes to perform complex statistical computations required for Machine Learning. You will gain information on statistics behind supervised learning, unsupervised learning, reinforcement learning, and more. Understand the real-world examples that discuss the statistical side of Machine Learning and familiarize yourself with it. You will also design programs for performing tasks such as model, parameter fitting, regression, classification, density collection, and more. By the end of the book, you will have mastered the required statistics for Machine Learning and will be able to apply your new skills to any sort of industry problem. Style and approach This practical, step-by-step guide will give you an understanding of the Statistical and Machine Learning fundamentals you'll need to build models.

Use scikit-learn to apply machine learning to real-world problems About This Book ? Master popular machine learning models including k-nearest neighbors, random forests, logistic regression, k-means, naive Bayes, and artificial neural networks ? Learn how to build and evaluate performance of efficient models using scikit-learn ? Practical guide to master your basics and learn from real life applications of machine learning Who This Book Is For This book is intended for software engineers who want to understand how common machine learning algorithms work and develop an intuition for how to use them, and for data scientists who want to learn about the scikit-learn API. Familiarity with machine learning fundamentals and Python are helpful, but not required. What You Will Learn ? Review fundamental concepts such as bias and variance ? Extract features from categorical variables, text, and images ? Predict the values of continuous variables using linear regression and K Nearest Neighbors ? Classify documents and images using logistic regression and support vector machines ? Create ensembles of estimators using bagging and boosting techniques ? Discover hidden structures in data using K-Means clustering ? Evaluate the performance of machine learning systems in common tasks In Detail Machine learning is the buzzword bringing computer science and statistics together to build smart and efficient models. Using powerful algorithms and techniques offered by machine learning you can automate any analytical model. This book examines a variety of machine learning models including popular machine learning algorithms such as k-nearest neighbors, logistic regression, naive Bayes, k-means, decision trees, and artificial neural networks. It discusses data preprocessing, hyperparameter optimization, and ensemble methods. You will build systems that classify documents, recognize images, detect ads, and more. You will learn to use scikit-learn’s API to extract features from categorical variables, text and images; evaluate model performance, and develop an intuition for how to improve your model’s performance. By the end of this book, you will master all required concepts of scikit-learn to build efficient models at work to carry out advanced tasks with the practical approach. Style and approach This book is motivated by the belief that you do not understand something until you can describe it simply. Work through toy problems to develop your understanding of the learning algorithms and models, then apply your learnings to real-life problems.

Harness the power of Scala to program Spark and analyze tonnes of data in the blink of an eye! About This Book ? Learn Scala’s sophisticated type system that combines Functional Programming and object-oriented concepts ? Work on a wide array of applications, from simple batch jobs to stream processing and machine learning ? Explore the most common as well as some complex use-cases to perform large-scale data analysis with Spark Who This Book Is For Anyone who wishes to learn how to perform data analysis by harnessing the power of Spark will find this book extremely useful. No knowledge of Spark or Scala is assumed, although prior programming experience (especially with other JVM languages) will be useful to pick up concepts quicker. What You Will Learn ? Understand object-oriented & functional programming concepts of Scala ? In-depth understanding of Scala collection APIs ? Work with RDD and DataFrame to learn Spark’s core abstractions ? Analysing structured and unstructured data using SparkSQL and GraphX ? Scalable and fault-tolerant streaming application development using Spark structured streaming ? Learn machine-learning best practices for classification, regression, dimensionality reduction, and recommendation system to build predictive models with widely used algorithms in Spark MLlib & ML ? Build clustering models to cluster a vast amount of data ? Understand tuning, debugging, and monitoring Spark applications ? Deploy Spark applications on real clusters in Standalone, Mesos, and YARN In Detail Scala has been observing wide adoption over the past few years, especially in the field of data science and analytics. Spark, built on Scala, has gained a lot of recognition and is being used widely in productions. Thus, if you want to leverage the power of Scala and Spark to make sense of big data, this book is for you. The first part introduces you to Scala, helping you understand the object-oriented and functional programming concepts needed for Spark application development. It then moves on to Spark to cover the basic abstractions using RDD and DataFrame. This will help you develop scalable and fault-tolerant streaming applications by analyzing structured and unstructured data using SparkSQL, GraphX, and Spark structured streaming. Finally, the book moves on to some advanced topics, such as monitoring, configuration, debugging, testing, and deployment. You will also learn how to develop Spark applications using SparkR and PySpark APIs, interactive data analytics using Zeppelin, and in-memory data processing with Alluxio. By the end of this book, you will have a thorough understanding of Spark, and you will be able to perform full-stack data analytics with a feel that no amount of data is too big. Style and approach Filled with practical examples and use cases, this book will hot only help you get up and running with Spark, but will also take you farther down the road to becoming a data scientist.

Advanced analytics on your Big Data with latest Apache Spark 2.x About This Book ? An advanced guide with a combination of instructions and practical examples to extend the most up-to date Spark functionalities. ? Extend your data processing capabilities to process huge chunk of data in minimum time using advanced concepts in Spark. ? Master the art of real-time processing with the help of Apache Spark 2.x Who This Book Is For If you are a developer with some experience with Spark and want to strengthen your knowledge of how to get around in the world of Spark, then this book is ideal for you. Basic knowledge of Linux, Hadoop and Spark is assumed. Reasonable knowledge of Scala is expected. What You Will Learn ? Examine Advanced Machine Learning and DeepLearning with MLlib, SparkML, SystemML, H2O and DeepLearning4J ? Study highly optimised unified batch and real-time data processing using SparkSQL and Structured Streaming ? Evaluate large-scale Graph Processing and Analysis using GraphX and GraphFrames ? Apply Apache Spark in Elastic deployments using Jupyter and Zeppelin Notebooks, Docker, Kubernetes and the IBM Cloud ? Understand internal details of cost based optimizers used in Catalyst, SystemML and GraphFrames ? Learn how specific parameter settings affect overall performance of an Apache Spark cluster ? Leverage Scala, R and python for your data science projects In Detail Apache Spark is an in-memory cluster-based parallel processing system that provides a wide range of functionalities such as graph processing, machine learning, stream processing, and SQL. This book aims to take your knowledge of Spark to the next level by teaching you how to expand Spark’s functionality and implement your data flows and machine/deep learning programs on top of the platform. The book commences with an overview of the Spark ecosystem. It will introduce you to Project Tungsten and Catalyst, two of the major advancements of Apache Spark 2.x. You will understand how memory management and binary processing, cache-aware computation, and code generation are used to speed things up dramatically. The book extends to show how to incorporate H20, SystemML, and Deeplearning4j for machine learning, and Jupyter Notebooks and Kubernetes/Docker for cloud-based Spark. During the course of the book, you will learn about the latest enhancements to Apache Spark 2.x, such as interactive querying of live data and unifying DataFrames and Datasets. You will also learn about the updates on the APIs and how DataFrames and Datasets affect SQL, machine learning, graph processing, and streaming. You will learn to use Spark as a big data operating system, understand how to implement advanced analytics on the new APIs, and explore how easy it is to use Spark in day-to-day tasks. Style and approach This book is an extensive guide to Apache Spark modules and tools and shows how Spark's functionality can be extended for real-time processing and storage with worked examples.

Over 60 hands-on recipes that get you acquainted with Drupal 8's features and help you harness its power About This Book ? Discover the enhanced content authoring experience that comes with Drupal 8 and how to customize it ? Take advantage of the broadened multilingual and tools of the new version to provide an internationalized website ? This step-by-step guide will show you how to deploy from development, staging, and production of a website with Drupal 8's brand new configuration management system Who This Book Is For The audience of the Drupal 8 Cookbook have been using Drupal and are ready to get a grasp of what to expect in Drupal 8. They have worked with Drupal as site builders, back-end developers, and front-end developers and are eager to see what awaits when they start using Drupal 8. This book will be a resource that allows them to get started and have a reference to building new applications with Drupal. What You Will Learn ? Extend Drupal through contributed or custom modules and themes ? Develop an internationalized website with Drupal's multilingual tools ? Integrate third-party front-end and back-end libraries with Drupal ? Turn Drupal into a web services provider using REST ? Create a mobile-first responsive Drupal application ? Run SimpleTest and PHPUnit to test Drupal ? Understand the plugin system that powers many of Drupal 8's new APIs to extend its functionality ? Get to grips with the mechanics of the configuration management system and the ability to import and export site configuration In Detail Began as a message board, Drupal today is open source software maintained and developed by a community of over 1,000,000 users and developers. Drupal is used by numerous local businesses to global corporations and diverse organizations all across the globe. With Drupal 8’s exciting features it brings, this book will be your go-to guide to experimenting with all of these features through helpful recipes. We’ll start by showing you how to customize and configure the Drupal environment as per your requirements, as well as how to install third-party libraries and then use them in the Drupal environment. Then we will move on to creating blocks and custom modules with the help of libraries. We will show you how to use the latest mobile-first feature of Drupal 8, which will help you make your apps responsive across all the major platforms. This book will also show you how to incorporate multilingual facilities in your sites, use web services and third-party plugins with your applications from inside Drupal 8, and test and deploy your apps. Style and approach This practical, recipe-based book will provide you with actionable techniques and methods to improve your existing Drupal development skills.

Over 100 hands-on recipes to build web applications easily and efficiently IN Spring 5.0 About This Book ? Solve real-world problems using the latest features of the Spring framework like Reactive Streams and the Functional Web Framework. ? Learn how to use dependency injection and aspect-oriented programming to write compartmentalized and testable code. ? Understand when to choose between Spring MVC and Spring Web Reactive for your projects Who This Book Is For Java developers who would like to gain in-depth knowledge of how to overcome problems that they face while developing great Spring applications. It will also cater to Spring enthusiasts, users and experts who need an arena for comparative analysis, new ideas and inquiries on some details regarding Spring 5.0 and its previous releases. A basic knowledge of Spring development is essential What You Will Learn ? Understand how functional programming and concurrency in JDK 1.9 works, and how it will affect Spring 5.0 ? Learn the importance and application of reactive programming in creating services, and also the process of creating asynchronous MVC applications ? Implement different Spring Data modules ? Integrate Spring Security to the container ? Create applications and deploy using Spring Boot ? Conceptualize the architecture behind Microservices and learn the details of its implementation ? Create different test cases for the components of Spring 5.0 components In Detail The Spring framework has been the go-to framework for Java developers for quite some time. It enhances modularity, provides more readable code, and enables the developer to focus on developing the application while the underlying framework takes care of transaction APIs, remote APIs, JMX APIs, and JMS APIs. The upcoming version of the Spring Framework has a lot to offer, above and beyond the platform upgrade to Java 9, and this book will show you all you need to know to overcome common to advanced problems you might face. Each recipe will showcase some old and new issues and solutions, right from configuring Spring 5.0 container to testing its components. Most importantly, the book will highlight concurrent processes, asynchronous MVC and reactive programming using Reactor Core APIs. Aside from the core components, this book will also include integration of third-party technologies that are mostly needed in building enterprise applications. By the end of the book, the reader will not only be well versed with the essential concepts of Spring, but will also have mastered its latest features in a solution-oriented manner. Style and Approach This book follows a cookbook style approach, presenting a problem and showing you how to overcome it with useful recipes. The examples provided will help you code along as you learn.

Use the two popular web development stacks, Node.js and MongoDB, to build full-featured web applications About This Book ? Learn the new ECMAScript along with Node 8 and MongoDB to make your application more effective. ? Get the up-to-date information required to launch your first application prototype using the latest versions of Node.js and MongoDB. ? A practical guide with clear instructions to designing and developing a complete web application from start to finish using trending frameworks such as angular4 and hapi Who This Book Is For The book is designed for JavaScript developers of any skill level who want to get up-and-running using Node.js and MongoDB to build full-featured web applications. A basic understanding of JavaScript and HTML is the only prerequisite for this book. What You Will Learn ? Work with Node.js building blocks ? Write and configure a web server using Node.js powered by the Express.js framework ? Build dynamic HTML pages using the Handlebars template engine ? Persist application data using MongoDB and Mongoose ODM ? Test your code using automated testing tools such as the Mocha framework ? Automate test cases using Gulp ? Reduce your web development time by integrating third-party tools for web interaction. ? Deploy a development environment to the cloud using services such as Heroku, Amazon Web Services, and Microsoft Azure ? Explore single-page application frameworks to take your web applications to the next level In Detail Node.js builds fast, scalable network applications while MongoDB is the perfect fit as a high-performance, open source NoSQL database solution. The combination of these two technologies offers high performance and scalability and helps in building fast, scalable network applications. Together they provide the power for manage any form of data as well as speed of delivery. This book will help you to get these two technologies working together to build web applications quickly and easily, with effortless deployment to the cloud. You will also learn about angular 4, which consumes pure JSON APOIs from a hapi server. The book begins by setting up your development environment, running you through the steps necessary to get the main application server up-and-running. Then you will see how to use Node.js to connect to a MongoDB database and perform data manipulations. From here on, the book will take you through integration with third-party tools to interact with web apps. You will see how to use controllers and view models to generate reusable code that will reduce development time. Toward the end, the book supplies tests to properly execute your code and take your skills to the next level with the most popular frameworks for developing web applications. By the end of the book, you will have a running web application developed with MongoDB, Node.js, and some of the most powerful and popular frameworks. Style and approach A practical guide with clear instructions to designing and developing a complete web application from start to finish

Learn the art of designing, implementing, and managing Cisco's networking solutions on datacenters, wirelessly, security and mobility to set up an Enterprise network. About This Book ? Implement Cisco's networking solutions on datacenters and wirelessly, Cloud, Security, and Mobility ? Leverage Cisco IOS to manage network infrastructures. ? A practical guide that will show how to troubleshoot common issues on the network. Who This Book Is For This book is targeted at network designers and IT engineers who are involved in designing, configuring, and operating enterprise networks, and are in taking decisions to make the necessary network changes to meet newer business needs such as evaluating new technology choices, enterprise growth, and adding new services on the network. The reader is expected to have a general understanding of the fundamentals of networking, including the OSI stack and IP addressing. What You Will Learn ? Understand the network lifecycle approach ? Get to know what makes a good network design ? Design components and technology choices at various places in the network (PINS) ? Work on sample configurations for network devices in the LAN/ WAN/ DC, and the wireless domain ? Get familiar with the configurations and best practices for securing the network ? Explore best practices for network operations In Detail Most enterprises use Cisco networking equipment to design and implement their networks. However, some networks outperform networks in other enterprises in terms of performance and meeting new business demands, because they were designed with a visionary approach. The book starts by describing the various stages in the network lifecycle and covers the plan, build, and operate phases. It covers topics that will help network engineers capture requirements, choose the right technology, design and implement the network, and finally manage and operate the network. It divides the overall network into its constituents depending upon functionality, and describe the technologies used and the design considerations for each functional area. The areas covered include the campus wired network, wireless access network, WAN choices, datacenter technologies, and security technologies. It also discusses the need to identify business-critical applications on the network, and how to prioritize these applications by deploying QoS on the network. Each topic provides the technology choices, and the scenario, involved in choosing each technology, and provides configuration guidelines for configuring and implementing solutions in enterprise networks. Style and approach A step-by-step practical guide that ensures you implement Cisco solutions such as enterprise networks, cloud, and data centers, on small-to-large organizations.

Simplify machine learning model implementations with Spark About This Book ? Solve the day-to-day problems of data science with Spark ? This unique cookbook consists of exciting and intuitive numerical recipes ? Optimize your work by acquiring, cleaning, analyzing, predicting, and visualizing your data Who This Book Is For This book is for Scala developers with a fairly good exposure to and understanding of machine learning techniques, but lack practical implementations with Spark. A solid knowledge of machine learning algorithms is assumed, as well as hands-on experience of implementing ML algorithms with Scala. However, you do not need to be acquainted with the Spark ML libraries and ecosystem. What You Will Learn ? Get to know how Scala and Spark go hand-in-hand for developers when developing ML systems with Spark ? Build a recommendation engine that scales with Spark ? Find out how to build unsupervised clustering systems to classify data in Spark ? Build machine learning systems with the Decision Tree and Ensemble models in Spark ? Deal with the curse of high-dimensionality in big data using Spark ? Implement Text analytics for Search Engines in Spark ? Streaming Machine Learning System implementation using Spark In Detail Machine learning aims to extract knowledge from data, relying on fundamental concepts in computer science, statistics, probability, and optimization. Learning about algorithms enables a wide range of applications, from everyday tasks such as product recommendations and spam filtering to cutting edge applications such as self-driving cars and personalized medicine. You will gain hands-on experience of applying these principles using Apache Spark, a resilient cluster computing system well suited for large-scale machine learning tasks. This book begins with a quick overview of setting up the necessary IDEs to facilitate the execution of code examples that will be covered in various chapters. It also highlights some key issues developers face while working with machine learning algorithms on the Spark platform. We progress by uncovering the various Spark APIs and the implementation of ML algorithms with developing classification systems, recommendation engines, text analytics, clustering, and learning systems. Toward the final chapters, we’ll focus on building high-end applications and explain various unsupervised methodologies and challenges to tackle when implementing with big data ML systems. Style and approach This book is packed with intuitive recipes supported with line-by-line explanations to help you understand how to optimize your work flow and resolve problems when working with complex data modeling tasks and predictive algorithms. This is a valuable resource for data scientists and those working on large scale data projects.

Leverage Scala and Machine Learning to study and construct systems that can learn from data About This Book ? Explore a broad variety of data processing, machine learning, and genetic algorithms through diagrams, mathematical formulation, and updated source code in Scala ? Take your expertise in Scala programming to the next level by creating and customizing AI applications ? Experiment with different techniques and evaluate their benefits and limitations using real-world applications in a tutorial style Who This Book Is For If you’re a data scientist or a data analyst with a fundamental knowledge of Scala who wants to learn and implement various Machine learning techniques, this book is for you. All you need is a good understanding of the Scala programming language, a basic knowledge of statistics, a keen interest in Big Data processing, and this book! What You Will Learn ? Build dynamic workflows for scientific computing ? Leverage open source libraries to extract patterns from time series ? Write your own classification, clustering, or evolutionary algorithm ? Perform relative performance tuning and evaluation of Spark ? Master probabilistic models for sequential data ? Experiment with advanced techniques such as regularization and kernelization ? Dive into neural networks and some deep learning architecture ? Apply some basic multiarm-bandit algorithms ? Solve big data problems with Scala parallel collections, Akka actors, and Apache Spark clusters ? Apply key learning strategies to a technical analysis of financial markets In Detail The discovery of information through data clustering and classification is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, engineering design, logistics, manufacturing, and trading strategies, to detection of genetic anomalies. The book is your one stop guide that introduces you to the functional capabilities of the Scala programming language that are critical to the creation of machine learning algorithms such as dependency injection and implicits. You start by learning data preprocessing and filtering techniques. Following this, you'll move on to unsupervised learning techniques such as clustering and dimension reduction, followed by probabilistic graphical models such as Na?ve Bayes, hidden Markov models and Monte Carlo inference. Further, it covers the discriminative algorithms such as linear, logistic regression with regularization, kernelization, support vector machines, neural networks, and deep learning. You’ll move on to evolutionary computing, multibandit algorithms, and reinforcement learning. Finally, the book includes a comprehensive overview of parallel computing in Scala and Akka followed by a de*ion of Apache Spark and its ML library. With updated codes based on the latest version of Scala and comprehensive examples, this book will ensure that you have more than just a solid fundamental knowledge in machine learning with Scala. Style and approach This book is designed as a tutorial with hands-on exercises using technical analysis of financial markets and corporate data. The approach of each chapter is such that it allows you to understand key concepts easily.