Expert techniques for building fast servers and scalable, real-time network applications with minimal effort; rewritten for Node.js 8 and Node.js 9 About This Book ? Packed with practical examples and explanations, Mastering Node.js contains everything you need to take your applications to the next level. ? Unleash the full potential of Node.js 9 to build real-time and scalable applications. ? Gain in-depth knowledge of asynchronous programming, event loops, and parallel data processing. ? Explore Node's innovative event-non-blocking design, and build professional applications with the help of detailed examples. Who This Book Is For This book is targeted at JavaScript developers who want to take an in-depth look at the latest Node.js framework to create faster, scalable, real-time backend applications. Basic JavaScript programming knowledge—and also some previous Node.js development experience—are mandatory to get the best out of this book What You Will Learn ? Build an Electron desktop app using Node that manages a filesystem ? Explore Streams and understand how they apply to building networked services ? Develop and deploy an SMS-driven customer service application ? Use WebSockets for rapid bi-directional communication ? Construct serverless applications with Amazon Lambda ? Test and debug with headless browsers, CPU profiling, Mocha, Sinon, and more ? Scale applications vertically and horizontally across multiple cores and web services In Detail Node.js, a modern development environment that enables developers to write server- and client-side code with JavaScript, thus becoming a popular choice among developers. This book covers the features of Node that are especially helpful to developers creating highly concurrent real-time applications. It takes you on a tour of Node's innovative event non-blocking design, showing you how to build professional applications. This edition has been updated to cover the latest features of Node 9 and ES6. All code examples and demo applications have been completely rewritten using the latest techniques, introducing Promises, functional programming, async/await, and other cutting-edge patterns for writing JavaScript code. Learn how to use microservices to simplify the design and composition of distributed systems. From building serverless cloud functions to native C++ plugins, from chatbots to massively scalable SMS-driven applications, you'll be prepared for building the next generation of distributed software. By the end of this book, you'll be building better Node applications more quickly, with less code and more power, and know how to run them at scale in production environments. Style and approach Mastering Node.js contains all of the examples and explanations you'll need to build applications in a short amount of time and at a low cost, running rapidly and at scale.

Design and build land, air, and sea drones using Ardupilot with Pixhawk 2.1 About This Book ? Explore the best practices used by the top industry professionals that will not only help you build drones in time, but also build effective solutions to cater to. ? Navigate through the complexities of Ardupilot to put together a complete functional UAV and assemble your drone ? Learn through practical examples that help you build robust UAV flight and ground control components Who This Book Is For The primary audience for this book is anyone (enthusiasts and hobbyists) who dream of building their own drones. It will also help those who are trying to build UAVs for commercial purposes. Some prior experience with microcontrollers and electronics would be useful. What You Will Learn ? Kitbash "dumb" objects into smart ones ? Program Pixhawk for your drones ? Fabricate your own parts out of different materials ? Integrate Pixhawk into different types of drones ? Build and understand the significant difference between land, sea, and air drones ? Adapt old Pixhawk sensors to the new Pixhawk 2.1 plugs ? Become familiar with procedures for testing your new drones In Detail The Ardupilot platform is an application ecosystem that encompasses various OS projects for drone programming, flight control, and advanced functionalities.The Ardupilot platform supports many Comms and APIs, such as DroneKit, ROS, and MAVLink. It unites OS drone projects to provide a common codebase. With the help of this book, you will have the satisfaction of building a drone from scratch and exploring its many recreational uses (aerial photography, playing, aerial surveillance, and so on). This book helps individuals and communities build powerful UAVs for both personal and commercial purposes. You will learn to unleash the Ardupilot technology for building, monitoring, and controlling your drones.This is a step-by-step guide covering practical examples and instructions for assembling a drone, building ground control unit using microcontrollers, QgroundControl, and MissionPlanner. You can further build robotic applications on your drone utilizing critical software libraries and tools from the ROS framework. With the help of DroneKit and MAVLink (for reliable communication), you can customize applications via cloud and mobile to interact with your UAV. Style and approach Step-by-step instructions to help assemble your first drone with the Ardupilot platform.

Learn how to leverage the features of the new Entity Framework Core APIs and use them to build pure .NET Core applications. About This Book ? Learn how to effectively manage your database to make it more productive and maintainable. ? Write simplified queries using LINQ to acquire the desired data easily ? Raise the abstraction level from data to objects so teams can function independently, resulting in easily maintainable code Who This Book Is For This book is for .NET Core developers who would like to integrate EF Core in their application. Prior knowledge of .NET Core and C# is assumed. What You Will Learn ? Create databases and perform CRUD operations on them ? Understand and build relationships (related to entities, keys, and properties) ? Understand in-built, custom, and remote validation (both client and server side) ? You will learn to handle concurrency to build responsive applications ? You will handle transactions and multi-tenancy while also improving performance In Detail Being able to create and maintain data-oriented applications has become crucial in modern programming. This is why Microsoft came up with Entity Framework so architects can optimize storage requirements while also writing efficient and maintainable application code. This book is a comprehensive guide that will show how to utilize the power of the Entity Framework to build efficient .NET Core applications. It not only teaches all the fundamentals of Entity Framework Core but also demonstrates how to use it practically so you can implement it in your software development. The book is divided into three modules. The first module focuses on building entities and relationships. Here you will also learn about different mapping techniques, which will help you choose the one best suited to your application design. Once you have understood the fundamentals of the Entity Framework, you will move on to learn about validation and querying in the second module. It will also teach you how to execute raw SQL queries and extend the Entity Framework to leverage Query Objects using the Query Object Pattern. The final module of the book focuses on performance optimization and managing the security of your application. You will learn to implement failsafe mechanisms using concurrency tokens. The book also explores row-level security and multitenant databases in detail. By the end of the book, you will be proficient in implementing Entity Framework on your .NET Core applications. Style and approach This book is filled with various examples that will help you use Entity Framework Core 2.0 to write efficient software.

Jump into the world of Game AI development About This Book ? Move beyond using libraries to create smart game AI, and create your own AI projects from scratch ? Implement the latest algorithms for AI development and in-game interaction ? Customize your existing game AI and make it better and more efficient to improve your overall game performance Who This Book Is For This book is for game developers with a basic knowledge of game development techniques and some basic programming techniques in C# or C++. What You Will Learn ? Get to know the basics of how to create different AI for different type of games ? Know what to do when something interferes with the AI choices and how the AI should behave if that happens ? Plan the interaction between the AI character and the environment using Smart Zones or Triggering Events ? Use animations correctly, blending one animation into another and rather than stopping one animation and starting another ? Calculate the best options for the AI to move using Pruning Strategies, Wall Distances, Map Preprocess Implementation, and Forced Neighbours ? Create Theta algorithms to the AI to find short and realistic looking paths ? Add many characters into the same scene and make them behave like a realistic crowd In Detail The book starts with the basics examples of AI for different game genres and directly jumps into defining the probabilities and possibilities of the AI character to determine character movement. Next, you’ll learn how AI characters should behave within the environment created. Moving on, you’ll explore how to work with animations. You’ll also plan and create pruning strategies, and create Theta algorithms to find short and realistic looking game paths. Next, you’ll learn how the AI should behave when there is a lot of characters in the same scene. You'll explore which methods and algorithms, such as possibility maps, Forward Chaining Plan, Rete Algorithm, Pruning Strategies, Wall Distances, and Map Preprocess Implementation should be used on different occasions. You’ll discover how to overcome some limitations, and how to deliver a better experience to the player. By the end of the book, you think differently about AI. Style and approach The book has a step-by-step tutorial style approach. The algorithms are explained by implementing them in #.

Over 80 recipes to help you improve vSphere 6.5's performance and solve problems before they arise About This Book ? The practical recipes provide cost-effective and high performance for any application running in a virtual machine ? Contains best practices and troubleshooting techniques to resolve vSphere 6.5 performance issues ? Get a comprehensive coverage of performance issues and solutions including vCenter Server design and virtual machine and application tuning Who This Book Is For If you are a system administrator and are planning to deploy vSphere 6.5 in your organization and want to maximize its performance, then this book is for you. Prior knowledge of the vSphere 6.5 concepts is essential. What You Will Learn ? Understand the VMM Scheduler, cache aware CPU Scheduler, NUMA aware CPU Scheduler, and more during the CPU Performance Design phase ? Get to know the virtual memory reclamation technique, host ballooning monitoring, and swapping activity ? Choose the right platform while designing your vCenter Server, redundant vCenter design, and vCenter SSO and its deployment ? Learn how to use various performance simulation tools ? Design VCSA Server Certificates to minimize security threats ? Use health check tools for storage and boost vSphere 6.5's performance with VAAI and VASA In Detail vSphere is a mission-critical piece of software for many businesses. It is a complex tool, and incorrect design and deployment can create performance related issues that can negatively affect the business. This book is focused on solving these problems as well as providing best practices and performance-enhancing techniques. This edition is fully updated to include all the new features in version 6.5 as well as the latest tools and techniques to keep vSphere performing at its best. This book starts with interesting recipes, such as the interaction of vSphere 6.5 components with physical layers such as CPU, memory, and networking. Then we focus on DRS, resource control design, and vSphere cluster design. Next, you'll learn about storage performance design and how it works with VMware vSphere 6.5. Moving on, you will learn about the two types of vCenter installation and the benefits of each. Lastly, the book covers performance tools that help you get the most out of your vSphere installation. By the end of this book, you will be able to identify, diagnose, and troubleshoot operational faults and critical performance issues in vSphere 6.5. Style and approach This cookbook is written in a practical, helpful style with numerous recipes focusing on answering and providing solutions to common and not-so-common performance issues and problems.

Make sense of your data and predict the unpredictable About This Book ? A unique book that centers around develop six key practical skills needed to develop and implement predictive analytics ? Apply the principles and techniques of predictive analytics to effectively interpret big data ? Solve real-world analytical problems with the help of practical case studies and real-world scenarios taken from the world of healthcare, marketing, and other business domains Who This Book Is For This book is for those with a mathematical/statistics background who wish to understand the concepts, techniques, and implementation of predictive analytics to resolve complex analytical issues. Basic familiarity with a programming language of R is expected. What You Will Learn ? Master the core predictive analytics algorithm which are used today in business ? Learn to implement the six steps for a successful analytics project ? Classify the right algorithm for your requirements ? Use and apply predictive analytics to research problems in healthcare ? Implement predictive analytics to retain and acquire your customers ? Use text mining to understand unstructured data ? Develop models on your own PC or in Spark/Hadoop environments ? Implement predictive analytics products for customers In Detail This is the go-to book for anyone interested in the steps needed to develop predictive analytics solutions with examples from the world of marketing, healthcare, and retail. We'll get started with a brief history of predictive analytics and learn about different roles and functions people play within a predictive analytics project. Then, we will learn about various ways of installing R along with their pros and cons, combined with a step-by-step installation of RStudio, and a de*ion of the best practices for organizing your projects. On completing the installation, we will begin to acquire the skills necessary to input, clean, and prepare your data for modeling. We will learn the six specific steps needed to implement and successfully deploy a predictive model starting from asking the right questions through model development and ending with deploying your predictive model into production. We will learn why collaboration is important and how agile iterative modeling cycles can increase your chances of developing and deploying the best successful model. We will continue your journey in the cloud by extending your skill set by learning about Databricks and SparkR, which allow you to develop predictive models on vast gigabytes of data. Style and Approach This book takes a practical hands-on approach wherein the algorithms will be explained with the help of real-world use cases. It is written in a well-researched academic style which is a great mix of theoretical and practical information. Code examples are supplied for both theoretical concepts as well as for the case studies. Key references and summaries will be provided at the end of each chapter so that you can explore those topics on their own.

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.

A guide to mastering Visual Studio 2017 About This Book ? Focus on coding with the new, improved, and powerful tools of VS 2017 ? Master improved debugging and unit testing support capabilities ? Accelerate cloud development with the built-in Azure tools Who This Book Is For .NET Developers who would like to master the new features of VS 2017, and would like to delve into newer areas such as cloud computing, would benefit from this book. Basic knowledge of previous versions of Visual Studio is assumed. What You Will Learn ? Learn what's new in the Visual Studio 2017 IDE, C# 7.0, and how it will help developers to improve their productivity ? Learn the workloads and components of the new installation wizard and how to use the online and offline installer ? Build stunning Windows apps using Windows Presentation Foundation (WPF) and Universal Windows Platform (UWP) tools ? Get familiar with .NET Core and learn how to build apps targeting this new framework ? Explore everything about NuGet packages ? Debug and test your applications using Visual Studio 2017 ? Accelerate cloud development with Microsoft Azure ? Integrate Visual Studio with most popular source control repositories, such as TFS and GitHub In Detail Visual Studio 2017 is the all-new IDE released by Microsoft for developers, targeting Microsoft and other platforms to build stunning Windows and web apps. Learning how to effectively use this technology can enhance your productivity while simplifying your most common tasks, allowing you more time to focus on your project. With this book, you will learn not only what VS2017 offers, but also what it takes to put it to work for your projects. Visual Studio 2017 is packed with improvements that increase productivity, and this book will get you started with the new features introduced in Visual Studio 2017 IDE and C# 7.0. Next, you will learn to use XAML tools to build classic WPF apps, and UWP tools to build apps targeting Windows 10. Later, you will learn about .NET Core and then explore NuGet, the package manager for the Microsoft development platform. Then, you will familiarize yourself with the debugging and live unit testing techniques that comes with the IDE. Finally, you'll adapt Microsoft's implementation of cloud computing with Azure, and the Visual Studio integration with Source Control repositories. Style and approach This comprehensive guide covers the advanced features of Visual Studio 2017, and communicates them through a practical approach to explore the underlying concepts of how, when, and why to use it.

Build, Manage and Improve your infrastructure effortlessly. About This Book ? An up-to-date and comprehensive resource on Terraform that lets you quickly and efficiently launch your infrastructure ? Learn how to implement your infrastructure as code and make secure, effective changes to your infrastructure ? Learn to build multi-cloud fault-tolerant systems and simplify the management and orchestration of even the largest scale and most complex cloud infrastructures Who This Book Is For This book is for developers and operators who already have some exposure to working with infrastructure but want to improve their workflow and introduce infrastructure as a code practice. Knowledge of essential Amazon Web Services components (EC2, VPC, IAM) would help contextualize the examples provided. Basic understanding of Jenkins and Shell *s will be helpful for the chapters on the production usage of Terraform. What You Will Learn ? Understand what Infrastructure as Code (IaC) means and why it matters ? Install, configure, and deploy Terraform ? Take full control of your infrastructure in the form of code ? Manage complete infrastructure, starting with a single server and scaling beyond any limits ? Discover a great set of production-ready practices to manage infrastructure ? Set up CI/CD pipelines to test and deliver Terraform stacks ? Construct templates to simplify more complex provisioning tasks In Detail Terraform is a tool used to efficiently build, configure, and improve the production infrastructure. It can manage the existing infrastructure as well as create custom in-house solutions. This book shows you when and how to implement infrastructure as a code practices with Terraform. It covers everything necessary to set up the complete management of infrastructure with Terraform, starting with the basics of using providers and resources. It is a comprehensive guide that begins with very small infrastructure templates and takes you all the way to managing complex systems, all using concrete examples that evolve over the course of the book. The book ends with the complete workflow of managing a production infrastructure as code—this is achieved with the help of version control and continuous integration. The readers will also learn how to combine multiple providers in a single template and manage different code bases with many complex modules. It focuses on how to set up continuous integration for the infrastructure code. The readers will be able to use Terraform to build, change, and combine infrastructure safely and efficiently. Style and approach This book will help and guide you to implement Terraform in your infrastructure. The readers will start by working on very small infrastructure templates and then slowly move on to manage complex systems, all by using concrete examples that will evolve during the course of the book.

This book covers the fundamentals of machine learning with Python in a concise and dynamic manner. It covers data mining and large-scale machine learning using Apache Spark. About This Book ? Take your first steps in the world of data science by understanding the tools and techniques of data analysis ? Train efficient Machine Learning models in Python using the supervised and unsupervised learning methods ? Learn how to use Apache Spark for processing Big Data efficiently Who This Book Is For If you are a budding data scientist or a data analyst who wants to analyze and gain actionable insights from data using Python, this book is for you. Programmers with some experience in Python who want to enter the lucrative world of Data Science will also find this book to be very useful, but you don't need to be an expert Python coder or mathematician to get the most from this book. What You Will Learn ? Learn how to clean your data and ready it for analysis ? Implement the popular clustering and regression methods in Python ? Train efficient machine learning models using decision trees and random forests ? Visualize the results of your analysis using Python’s Matplotlib library ? Use Apache Spark’s MLlib package to perform machine learning on large datasets In Detail Join Frank Kane, who worked on Amazon and IMDb’s machine learning algorithms, as he guides you on your first steps into the world of data science. Hands-On Data Science and Python Machine Learning gives you the tools that you need to understand and explore the core topics in the field, and the confidence and practice to build and analyze your own machine learning models. With the help of interesting and easy-to-follow practical examples, Frank Kane explains potentially complex topics such as Bayesian methods and K-means clustering in a way that anybody can understand them. Based on Frank’s successful data science course, Hands-On Data Science and Python Machine Learning empowers you to conduct data analysis and perform efficient machine learning using Python. Let Frank help you unearth the value in your data using the various data mining and data analysis techniques available in Python, and to develop efficient predictive models to predict future results. You will also learn how to perform large-scale machine learning on Big Data using Apache Spark. The book covers preparing your data for analysis, training machine learning models, and visualizing the final data analysis. Style and approach This comprehensive book is a perfect blend of theory and hands-on code examples in Python which can be used for your reference at any time.

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.

Leverage the power of Python to collect, process, and mine deep insights from social media data About This Book ? Acquire data from various social media platforms such as Facebook, Twitter, YouTube, GitHub, and more ? Analyze and extract actionable insights from your social data using various Python tools ? A highly practical guide to conducting efficient social media analytics at scale Who This Book Is For If you are a programmer or a data analyst familiar with the Python programming language and want to perform analyses of your social data to acquire valuable business insights, this book is for you. The book does not assume any prior knowledge of any data analysis tool or process. What You Will Learn ? Understand the basics of social media mining ? Use PyMongo to clean, store, and access data in MongoDB ? Understand user reactions and emotion detection on Facebook ? Perform Twitter sentiment analysis and entity recognition using Python ? Analyze video and campaign performance on YouTube ? Mine popular trends on GitHub and predict the next big technology ? Extract conversational topics on public internet forums ? Analyze user interests on Pinterest ? Perform large-scale social media analytics on the cloud In Detail Social Media platforms such as Facebook, Twitter, Forums, Pinterest, and YouTube have become part of everyday life in a big way. However, these complex and noisy data streams pose a potent challenge to everyone when it comes to harnessing them properly and benefiting from them. This book will introduce you to the concept of social media analytics, and how you can leverage its capabilities to empower your business. Right from acquiring data from various social networking sources such as Twitter, Facebook, YouTube, Pinterest, and social forums, you will see how to clean data and make it ready for analytical operations using various Python APIs. This book explains how to structure the clean data obtained and store in MongoDB using PyMongo. You will also perform web scraping and visualize data using Scrappy and Beautifulsoup. Finally, you will be introduced to different techniques to perform analytics at scale for your social data on the cloud, using Python and Spark. By the end of this book, you will be able to utilize the power of Python to gain valuable insights from social media data and use them to enhance your business processes. Style and approach This book follows a step-by-step approach to teach readers the concepts of social media analytics using the Python programming language. To explain various data analysis processes, real-world datasets are used wherever required.

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.

Learn the techniques used by the most successful IT people in the world. About This Book ? Get real-life case studies for different IT roles, developers, testers, analysts, project managers, DBAs ? Identify with your IT scenarios and take the right decision to move up in your career ? Improve your EQ and face any difficult scenario confidently and effectively Who This Book Is For This book is for professionals across the IT domain who work as developers, administrators, architects, administrators system analysts, and so on, who want to create a better working environment around them by improving their own emotional intelligence. This book assumes that you are a beginner to emotional intelligence and will help you understand the basic concepts before helping you with real life scenarios. What You Will Learn ? Improve your observation skills to understand people better ? Know how to identify what motivates you and those around you ? Develop strategies for working more effectively with others ? Increase your capacity to influence people and improve your communication skills ? Understand how to successfully complete tasks through other people ? Discover how to control the emotional content of your decision-making In Detail This book will help you discover your emotional quotient (EQ) through practices and techniques that are used by the most successful IT people in the world. It will make you familiar with the core skills of Emotional Intelligence, such as understanding the role that emotions play in life, especially in the workplace. You will learn to identify the factors that make your behavior consistent, not just to other employees, but to yourself. This includes recognizing, harnessing, predicting, fostering, valuing, soothing, increasing, decreasing, managing, shifting, influencing or turning around emotions and integrating accurate emotional information into decision-making, reasoning, problem solving, etc., because, emotions run business in a way that spreadsheets and logic cannot. When a deadline lurks, you’ll know the steps you need to take to keep calm and composed. You’ll find out how to meet the deadline, and not get bogged down by stress. We’ll explain these factors and techniques through real-life examples faced by IT employees and you’ll learn using the choices that they made. This book will give you a detailed analysis of the events and behavioral pattern of the employees during that time. This will help you improve your own EQ to the extent that you don’t just survive, but thrive in a competitive IT industry. Style and approach You will be taken through real-life events faced by IT employees in different scenarios. These real-world cases are analyzed along with the response of the employees, which will help you to develop your own emotion intelligence quotient and face any difficult scenario confidently and effectively.

Over 50 recipes on the core features of Apache Mesos and running big data frameworks in Mesos About This Book ? Learn to install and configure Mesos to suit the needs of your organization ? Follow step-by-step instructions to deploy application frameworks on top of Mesos, saving you many hours of research and trial and error ? Use this practical guide packed with powerful recipes to implement Mesos and easily integrate it with other application frameworks Who This Book Is For This book is for system administrators, engineers, and big data programmers. Basic experience with big data technologies such as Hadoop or Spark would be useful but is not essential. A working knowledge of Apache Mesos is expected. What You Will Learn ? Set up Mesos on different operating systems ? Use the Marathon and Chronos frameworks to manage multiple applications ? Work with Mesos and Docker ? Integrate Mesos with Spark and other big data frameworks ? Use networking features in Mesos for effective communication between containers ? Configure Mesos for high availability using Zookeeper ? Secure your Mesos clusters with SASL and Authorization ACLs ? Solve everyday problems and discover the best practices In Detail Apache Mesos is open source cluster sharing and management software. Deploying and managing scalable applications in large-scale clustered environments can be difficult, but Apache Mesos makes it easier with efficient resource isolation and sharing across application frameworks. The goal of this book is to guide you through the practical implementation of the Mesos core along with a number of Mesos supported frameworks. You will begin by installing Mesos and then learn how to configure clusters and maintain them. You will also see how to deploy a cluster in a production environment with high availability using Zookeeper. Next, you will get to grips with using Mesos, Marathon, and Docker to build and deploy a PaaS. You will see how to schedule jobs with Chronos. We’ll demonstrate how to integrate Mesos with big data frameworks such as Spark, Hadoop, and Storm. Practical solutions backed with clear examples will also show you how to deploy elastic big data jobs. You will find out how to deploy a scalable continuous integration and delivery system on Mesos with Jenkins. Finally, you will configure and deploy a highly scalable distributed search engine with ElasticSearch. Throughout the course of this book, you will get to know tips and tricks along with best practices to follow when working with Mesos. Style and approach This step-by-step guide is packed with powerful recipes on using Apache Mesos and shows its integration with containers and big data frameworks.

Leverage the power of PowerShell to bring the best out of your AWS infrastructure About This Book ? A collection of real-world-tested Powershell *s that can be used to manage your Windows server efficiently ? Follow step-by-step processes to solve your problems with Windows servers using AWS tools ? Design examples that work in the Amazon free usage tier, which lets you run the Windows platform on cloud Who This Book Is For This book will be useful for (but not limited to) Windows System administrators, cloud engineers, architects, DevOps engineers, and all those who want to accomplish tasks on the AWS Public Cloud using PowerShell. What You Will Learn ? Install the AWS Tools for PowerShell 6 ? Understand key services provided by Amazon Web services (AWS) ? Understand the Virtual Private Cloud ? Use PowerShell 6 for AWS Identity and Access Management (IAM) ? Use PowerShell 6 for AWS Elastic Compute Cloud (EC2) ? Use PowerShell 6 for AWS Simple Storage Service (S3) ? Use PowerShell 6 for AWS Relational Database Service (RDS) ? Build fault-tolerant and highly-available applications using PowerShell 6 In Detail AWS Tools for PowerShell 6 shows you exactly how to automate all the aspects of AWS. You can take advantage of the amazing power of the cloud, yet add powerful *s and mechanisms to perform common tasks faster than ever before. This book expands on the Amazon documentation with real-world, useful examples and production-ready *s to automate all the aspects of your new cloud platform. It will cover topics such as managing Windows with PowerShell, setting up security services, administering database services, and deploying and managing networking. You will also explore advanced topics such as PowerShell authoring techniques, and configuring and managing storage and content delivery. By the end of this book, you will be able to use Amazon Web Services to automate and manage Windows servers. You will also have gained a good understanding of automating the AWS infrastructure using simple coding. Style and approach This step-by-step guide starts with simple examples then expands to full-blown administrative tasks leading to the efficient management of Windows servers. Each topic covers a section related to Amazon Web Services products, and the examples are built on one another to deliver a comprehensive library of *s for administrators.

Discover how to build full stack web applications with the Raspberry Pi 3 About This Book ? Leverage JavaScript, HTML5, and Cloud APIs to create visual representations and interactive web pages. ? Learn to install and use a Node.js-based web framework to develop Raspberry Pi 3-powered web applications. ? A step-by-step guide that will cover from setting up a embedded system to developing embedded, device-powered interactive web applications. Who This Book Is For This book is aimed at hobbyist, enthusiasts, and developers eager to develop embedded device-powered web applications. Prior programming experience with JavaScript, HTML5, and Node.JS will be beneficial. What You Will Learn ? Get up and running with your Raspberry Pi ? Go full stack! Learn about the end-to-end development process for web applications, right from the OS up to the actual HTML web interface ? Discover that JavaScript is one of the fastest growing languages today, and is the only language that can be used both on a browser and server. This book will empower you to develop in a complete JavaScript stack ? See that the IoT is everywhere!Connect your application to the outside world. Make use of sensors in your Raspberry Pi to give your application an edge, and unleash the full power of the Internet of Things ? Build a rich UI with beautiful charts and data visualizations that can run on any browser ? Make your software data-driven. Learn how to utilize SQLite to collect and analyze data from multiple systems In Detail Modern web technology and portable computing together have enabled huge advances in the Internet of Things (IoT) space,as well as in areas such as machine learning and big data. The Raspberry Pi is a very popular portable computer for running full stack web applications. This book will empower you to master this rapidly evolving technology to develop complex web applications and interfaces. This book starts by familiarizing you with the various components that make up the web development stack and that will integrate into your Raspberry Pi-powered web applications. It also introduces the Raspberry Pi computer and teach you how to get up and running with a brand new one. Next, this book introduces you to the different kinds of sensor you’ll use to make your applications; using these skills, you will be able to create full stack web applications and make them available to users via a web interface. Later, this book will also teach you how to build interactive web applications using JavaScript and HTML5 for the visual representation of sensor data. Finally, this book will teach you how to use a SQLite database to store and retrieve sensor data from multiple Raspberry Pi computers. By the end of this book you will be able to create complex full stack web applications on the Raspberry Pi 3 and will have improved your application’s performance and usability. Style and approach Step-by-step instructions on developing a full stack web application and deploying it to the Cloud.

Learn how to build advanced reports and dashboards in Salesforce Lightning experience About This Book ? Visualize and create advanced reports and dashboards using Lightning Experience ? Improve overall business efficiency with advanced and effective reports and dashboards ? Understand and create custom reports and dashboards Who This Book Is For This book is targeted at Salesforce.com administrators, business analysts, and managers who use Salesforce.com for their daily job and want to learn in depth about Salesforce Reporting and Dashboard in Lightning Experience. Readers should have a basic knowledge of Salesforce, such as: Accounts, Contacts, Leads, Opportunities and custom objects. What You Will Learn ? Navigate in Salesforce.com within the Lightning Experience user interface ? Secure and share your reports and dashboards with other users ? Create, manage, and maintain reports using Report Builder ? Learn how the report type can affect the report generated ? Explore the report and dashboard folder and the sharing model ? Create reports with multiple formats and custom report types ? Explore various dashboard features in Lightning Experience ? Use Salesforce1, including accessing reports and dashboards In Detail Built on the Salesforce App Cloud, the new Lightning Experience combines the new Lightning Design System, Lightning App Builder, and Lightning Components to enable anyone to quickly and easily create modern enterprise apps. The book will start with a gentle introduction to the basics of Salesforce reports and dashboards. It will also explain how to access reports in depth. Then you will learn how to create and manage reports, to use Schedule Report, and create advanced report configurations. The next section talks about dashboards and will enable you to understand and compare various types of dashboard component and how you can benefit the most from each of them. Then we move on to advanced topics and explain tips and tricks related to reports and dashboards, including reporting snapshots, report parameters, and collaboration. Finally, we will discuss how to access dashboards and reports from the Salesforce1 mobile app. Style and approach This comprehensive guide covers the advanced features of the all new Salesforce Lightning concepts and communicates them through a practical approach to explore the underlying concepts of how, when, and why to use them.