Build, design and improve advanced business intelligence solutions using Tableau’s latest features, including Tableau Prep, Tableau Hyper, and Tableau Server Key Features * Master new features in Tableau 2019.1 to solve real-world analytics challenges * Perform Geo-Spatial Analytics, Time Series Analysis, and self-service analytics using real-life examples * Build and publish dashboards and explore storytelling using Python and MATLAB integration support Book Description Tableau is one of the leading business intelligence (BI) tools used to solve BI and analytics challenges. With this book, you will master Tableau's features and offerings in various paradigms of the BI domain. This book is also the second edition of the popular Mastering Tableau series, with new features, examples, and updated code. The book covers essential Tableau concepts and its advanced functionalities. Using Tableau Hyper and Tableau Prep, you’ll be able to handle and prepare data easily. You’ll gear up to perform complex joins, spatial joins, union, and data blending tasks using practical examples. Following this, you’ll learn how to perform data densification to make displaying granular data easier. Next, you’ll explore expert-level examples to help you with advanced calculations, mapping, and visual design using various Tableau extensions. With the help of examples, you’ll also learn about improving dashboard performance, connecting Tableau Server, and understanding data visualizations. In the final chapters, you’ll cover advanced use cases such as Self-Service Analytics, Time Series Analytics, and Geo-Spatial Analytics, and learn to connect Tableau to R, Python, and MATLAB. By the end of this book, you’ll have mastered the advanced offerings of Tableau and be able to tackle common and not-so-common challenges faced in the BI domain. What you will learn * Get up to speed with various Tableau components * Master data preparation techniques using Tableau Prep * Discover how to use Tableau to create a PowerPoint-like presentation * Understand different Tableau visualization techniques and dashboard designs * Interact with the Tableau server to understand its architecture and functionalities * Study advanced visualizations and dashboard creation techniques * Brush up on powerful Self-Service Analytics, Time Series Analytics, and Geo-Spatial Analytics Who this book is for This book is designed for business analysts, BI professionals and data analysts who want to master Tableau to solve a range of data science and business intelligence problems. The book is ideal if you have a good understanding of Tableau and want to take your skills to the next level.

Implement neural network architectures by building them from scratch for multiple real-world applications. Key Features * From scratch, build multiple neural network architectures such as CNN, RNN, LSTM in Keras * Discover tips and tricks for designing a robust neural network to solve real-world problems * Graduate from understanding the working details of neural networks and master the art of fine-tuning them Book Description This book will take you from the basics of neural networks to advanced implementations of architectures using a recipe-based approach. We will learn about how neural networks work and the impact of various hyper parameters on a network's accuracy along with leveraging neural networks for structured and unstructured data. Later, we will learn how to classify and detect objects in images. We will also learn to use transfer learning for multiple applications, including a self-driving car using Convolutional Neural Networks. We will generate images while leveraging GANs and also by performing image encoding. Additionally, we will perform text analysis using word vector based techniques. Later, we will use Recurrent Neural Networks and LSTM to implement chatbot and Machine Translation systems. Finally, you will learn about transcribing images, audio, and generating captions and also use Deep Q-learning to build an agent that plays Space Invaders game. By the end of this book, you will have developed the skills to choose and customize multiple neural network architectures for various deep learning problems you might encounter. What you will learn * Build multiple advanced neural network architectures from scratch * Explore transfer learning to perform object detection and classification * Build self-driving car applications using instance and semantic segmentation * Understand data encoding for image, text and recommender systems * Implement text analysis using sequence-to-sequence learning * Leverage a combination of CNN and RNN to perform end-to-end learning * Build agents to play games using deep Q-learning Who this book is for This intermediate-level book targets beginners and intermediate-level machine learning practitioners and data scientists who have just started their journey with neural networks. This book is for those who are looking for resources to help them navigate through the various neural network architectures; you'll build multiple architectures, with concomitant case studies ordered by the complexity of the problem. A basic understanding of Python programming and a familiarity with basic machine learning are all you need to get started with this book.

Discover advanced virtualization techniques and strategies to deliver centralized desktop and application services Key Features * Leverage advanced desktop virtualization techniques and strategies to transform your organization * Build better virtualized services for your users with VMware Horizon 7.8 * Develop and deploy end-to-end virtualized solutions Book Description Desktop virtualization can be tough, but VMware Horizon 7.8 changes all that. With a rich and adaptive UX, improved security,and a range of useful features for storage and networking optimization, there's plenty to love. But to properly fall in love with it, you need to know how to use it, and that means venturing deeper into the software and taking advantage of its extensive range of features, many of which are underused and underpromoted. This guide will take you through everything you need to know to not only successfully virtualize your desktop infrastructure, but also to maintain and optimize it to keep all your users happy. We'll show you how to assess and analyze your infrastructure, and how to use that analysis to design a solution that meets your organizational and user needs. Once you've done that, you'll find out how to build your virtualized environment, before deploying your virtualized solution. But more than that,we'll also make sure you know everything you need to know about the full range of features on offer, including the mobile cloud, so that you can use them to take full control of your virtualized infrastructure. What you will learn * Successfully configure Horizon 7.8 for the needs of your users * Deliver virtual desktops, session-based desktops, and hosted applications * Become familiar with how to develop, and deploy, a complete, end-to-end solution * Discover how to optimize desktop OS images for virtual desktops * Build, optimize, and tune desktop operating systems to deliver a superior end user experience * Explore the Horizon 7.8 infrastructure so that you can take full advantage of it Who this book is for This book is ideal for system admins, and solution architects interested in gaining hands-on experience with virtualization. It will take you to an advanced level, but at a pace that ensures you are always solving real-world problems. Some experience in desktop management using Windows and Microsoft Office (and familiarity with Active Directory, SQL, Windows Remote Desktop Session Hosting, and VMware vSphere technology) is necessary.

Design interactive graphics and visuals for your data-driven applications using the popular open-source Chart.js data visualization library. Key Features * Harness the power of JavaScript, HTML, and CSS to create interactive visualizations * Display quantitative information efficiently in the form of attractive charts by using Chart.js * A practical guide for creating data-driven applications using open-source JavaScript library Book Description Chart.js is a free, open-source data visualization library, maintained by an active community of developers in GitHub, where it rates as the second most popular data visualization library. If you want to quickly create responsive Web-based data visualizations for the Web, Chart.js is a great choice. This book guides the reader through dozens of practical examples, complete with code you can run and modify as you wish. It is a practical hands-on introduction to Chart.js. If you have basic knowledge of HTML, CSS and JavaScript you can learn to create beautiful interactive Web Canvas-based visualizations for your data using Chart.js. This book will help you set up Chart.js in a Web page and show how to create each one of the eight Chart.js chart types. You will also learn how to configure most properties that override Chart’s default styles and behaviors. Practical applications of Chart.js are exemplified using real data files obtained from public data portals. You will learn how to load, parse, filter and select the data you wish to display from those files. You will also learn how to create visualizations that reveal patterns in the data. This book is based on Chart.js version 2.7.3 and ES2015 JavaScript. By the end of the book, you will be able to create beautiful, efficient and interactive data visualizations for the Web using Chart.js. What you will learn * Learn how to create interactive and responsive data visualizations using Chart.js * Learn how to create Canvas-based graphics without Canvas programming * Create composite charts and configure animated data updates and transitions * Efficiently display quantitative information using bar and line charts, scatterplots, and pie charts * Learn how to load, parse, and filter external files in JSON and CSV formats * Understand the benefits of using a data visualization framework Who this book is for The ideal target audience of this book includes web developers and designers, data journalists, data scientists and artists who wish to create interactive data visualizations for the Web. Basic knowledge of HTML, CSS, and JavaScript is required. No Canvas knowledge is necessary.

Enhance your development skills with Java’s state-of-the-art features and projects to make your applications leaner and faster Key Features * Overcome the challenges involved in migrating to new versions of Java * Discover how Oracle has bridged the gap between Java and native code * Make the best use of new Java features and libraries in your applications Book Description With its new six-monthly release cadence, Java is moving forward faster. In addition to planned version releases, a lot of work is currently being undertaken on various Java projects at Oracle. In order to make best use of the new features in their applications and libraries, you must be well-versed with the most recent advancements. Java 11 and 12 – New Features will take you through the latest developments in Java, right from variable type inference and simplified multithreading through to performance improvements, which are covered in depth to help you make your applications more efficient. This book explains the relevance and applicability of Java's new features, and answers your questions on whether to invest in migrating to new Java versions and when to migrate. You'll also get to grips with platform features, such as AppCDS and new garbage collectors, to tune and optimize your application—from reduced launch time and latency to improved performance and throughput. By the end of this book, you will be equipped with a thorough understanding of the new features of Java 11, 12, and Project Amber, and possess the skills to apply them with a view to improving your application's performance. What you will learn * Study type interference and how to work with the var type * Understand Class-Data Sharing, its benefits, and limitations * Discover platform options to reduce your application’s launch time * Improve application performance by switching garbage collectors * Get up to date with the new Java release cadence * Define and assess decision criteria for migrating to a new version of Java Who this book is for If you’re an executive or solutions architect responsible for technology selection or Java migration decisions, this Java book is for you. You’ll also benefit from this book if you’re a computer science enthusiast curious to learn about the latest and upcoming Java features. This book will help you migrate your solutions from Java 8 or older to the latest Java release.

Master a range of machine learning domains with real-world projects using TensorFlow for R, H2O, MXNet, and more Key Features *Master machine learning, deep learning, and predictive modeling concepts in R 3.5 *Build intelligent end-to-end projects for finance, retail, social media, and a variety of domains *Implement smart cognitive models with helpful tips and best practices Book Description R is one of the most popular languages when it comes to performing computational statistics (statistical computing) easily and exploring the mathematical side of machine learning. With this book, you will leverage the R ecosystem to build efficient machine learning applications that carry out intelligent tasks within your organization. This book will help you test your knowledge and skills, guiding you on how to build easily through to complex machine learning projects. You will first learn how to build powerful machine learning models with ensembles to predict employee attrition. Next, you’ll implement a joke recommendation engine and learn how to perform sentiment analysis on Amazon reviews. You’ll also explore different clustering techniques to segment customers using wholesale data. In addition to this, the book will get you acquainted with credit card fraud detection using autoencoders, and reinforcement learning to make predictions and win on a casino slot machine. By the end of the book, you will be equipped to confidently perform complex tasks to build research and commercial projects for automated operations. What you will learn *Explore deep neural networks and various frameworks that can be used in R *Develop a joke recommendation engine to recommend jokes that match users’ tastes *Create powerful ML models with ensembles to predict employee attrition *Build autoencoders for credit card fraud detection *Work with image recognition and convolutional neural networks *Make predictions for casino slot machine using reinforcement learning *Implement NLP techniques for sentiment analysis and customer segmentation Who this book is for If you’re a data analyst, data scientist, or machine learning developer who wants to master machine learning concepts using R by building real-world projects, this is the book for you. Each project will help you test your skills in implementing machine learning algorithms and techniques. A basic understanding of machine learning and working knowledge of R programming is necessary to get the most out of this book.

Learn advanced state-of-the-art deep learning techniques and their applications using popular Python libraries Key Features *Build a strong foundation in neural networks and deep learning with Python libraries *Explore advanced deep learning techniques and their applications across computer vision and NLP *Learn how a computer can navigate in complex environments with reinforcement learning Book Description With the surge in artificial intelligence in applications catering to both business and consumer needs, deep learning is more important than ever for meeting current and future market demands. With this book, you’ll explore deep learning, and learn how to put machine learning to use in your projects. This second edition of Python Deep Learning will get you up to speed with deep learning, deep neural networks, and how to train them with high-performance algorithms and popular Python frameworks. You’ll uncover different neural network architectures, such as convolutional networks, recurrent neural networks, long short-term memory (LSTM) networks, and capsule networks. You’ll also learn how to solve problems in the fields of computer vision, natural language processing (NLP), and speech recognition. You'll study generative model approaches such as variational autoencoders and Generative Adversarial Networks (GANs) to generate images. As you delve into newly evolved areas of reinforcement learning, you’ll gain an understanding of state-of-the-art algorithms that are the main components behind popular games Go, Atari, and Dota. By the end of the book, you will be well-versed with the theory of deep learning along with its real-world applications. What you will learn *Grasp the mathematical theory behind neural networks and deep learning processes *Investigate and resolve computer vision challenges using convolutional networks and capsule networks *Solve generative tasks using variational autoencoders and Generative Adversarial Networks *Implement complex NLP tasks using recurrent networks (LSTM and GRU) and attention models *Explore reinforcement learning and understand how agents behave in a complex environment *Get up to date with applications of deep learning in autonomous vehicles Who this book is for This book is for data science practitioners, machine learning engineers, and those interested in deep learning who have a basic foundation in machine learning and some Python programming experience. A background in mathematics and conceptual understanding of calculus and statistics will help you gain maximum benefit from this book.

Write high-level abstractions while retaining full control of the hardware, performances, and maintainability. Key Features * Transform your ideas into modern C++ code, with both C++11 and C++17 * Explore best practices for creating high-performance solutions * Understand C++ basics and work with concrete real-world examples Book Description C++ Fundamentals begins by introducing you to the C++ syntax. You will study the semantics of variables along with their advantages and trade-offs, and see how they can be best used to write safe and efficient code. With the help of this book, you’ll be able to compile fully working C++ programs and understand how variables, references, and pointers can be used to manipulate the state of the program. Then you'll explore functions and classes — the features that C++ offers to organize a program — and use them to solve more complex problems such as functions and classes. You’ll also understand common pitfalls and modern best practices, especially the ones that diverge from the C++98 guideline. As you advance through the chapters, you’ll study the advantages of generic programming and write your own templates to make generic algorithms that work with any type. This C++ book will guide you in fully exploiting standard containers and understanding how to pick the appropriate container for each problem. You will even work with a variety of memory management tools in C++. By the end of this book, you will not only be able to write efficient code, but also be equipped to improve the readability, performance, and maintainability of your programs using standard algorithms. What you will learn * Work with the C++ compilation model and syntaxes * Apply best practices for writing functions and classes * Write safe, generic, and efficient code with templates * Explore the containers that C++ standard offers * Discover the new paradigms introduced with C++11, C++14, and C++17 * Get to grips with the core language features of C++ * Abstract complex problems using object-oriented programming in C++ Who this book is for If you’re a developer looking to learn a new powerful language or are familiar with C++ but want to update your knowledge with modern paradigms of C++11, C++14, and C++17, this book is for you. To easily understand the concepts in the book, you must be familiar with the basics of programming.

Enhance your career options with this well-crafted object-oriented programming language that enjoys the support of an enormous ecosystem of tools and libraries Key Features * Get introduced to Java, its features, and its ecosystem * Understand how Java uses object-oriented programming * Become an expert Java exception handler Book Description Since its inception, Java has stormed the programming world. Its features and functionalities provide developers with the tools needed to write robust cross-platform applications. Java Fundamentals introduces you to these tools and functionalities that will enable you to create Java programs. The book begins with an introduction to the language, its philosophy, and evolution over time, until the latest release. You'll learn how the javac/java tools work and what Java packages are - the way a Java program is usually organized. Once you are comfortable with this, you'll be introduced to advanced concepts of the language, such as control flow keywords. You'll explore object-oriented programming and the part it plays in making Java what it is. In the concluding chapters, you'll get to grips with classes, typecasting, and interfaces, and understand the use of data structures, arrays, strings, handling exceptions, and creating generics. By the end of this book, you will have learned to write programs, automate tasks, and follow advanced courses on algorithms and data structures or explore more advanced Java courses. What you will learn * Create and run Java programs * Use data types, data structures, and control flow in your code * Implement best practices while creating objects * Work with constructors and inheritance * Understand advanced data structures to organize and store data * Employ generics for stronger check-types during compilation * Learn to handle exceptions in your code Who this book is for Java Fundamentals is designed for tech enthusiasts who are familiar with some programming languages and want a quick introduction to the most important principles of Java.

A step-by-step guide that will help you design, develop, scale, and deploy RESTful APIs with TypeScript 3 and Node.js Key Features * Gain in-depth knowledge of OpenAPI and Swagger to build scalable web services * Explore a variety of test frameworks and test runners such as Stryker, Mocha, and Chai * Create a pipeline by Dockerizing your environment using Travis CI, Google Cloud Platform, and GitHub Book Description In the world of web development, leveraging data is the key to developing comprehensive applications, and RESTful APIs help you to achieve this systematically. This book will guide you in designing and developing web services with the power of TypeScript 3 and Node.js. You'll design REST APIs using best practices for request handling, validation, authentication, and authorization. You'll also understand how to enhance the capabilities of your APIs with ODMs, databases, models and views, as well as asynchronous callbacks. This book will guide you in securing your environment by testing your services and initiating test automation with different testing approaches. Furthermore, you'll get to grips with developing secure, testable, and more efficient code, and be able to scale and deploy TypeScript 3 and Node.js-powered RESTful APIs on cloud platforms such as the Google Cloud Platform. Finally, the book will help you explore microservices and give you an overview of what GraphQL can allow you to do. By the end of this book, you will be able to use RESTful web services to create your APIs for mobile and web apps and other platforms. What you will learn * Explore various methods to plan your services in a scalable way * Understand how to handle different request types and the response status code * Get to grips with securing web services * Delve into error handling and logging your web services for improved debugging * Uncover the microservices architecture and GraphQL * Create automated CI/CD pipelines for release and deployment strategies Who this book is for If you’re a developer who has a basic understanding of REST concepts and want to learn how to design and develop RESTful APIs, this book is for you. Prior knowledge of TypeScript will help you make the most out of this book.

A practical guide that helps you progress to using modern integration methods and leverage new cloud capability models Key Features * Design critical hybrid integration solutions for your organization * Gain in-depth knowledge of how to build cloud-native integration solutions * Leverage cognitive services to build smart cloud solutions Book Description With more enterprises adapting cloud-based and API-based solutions, application integration has become more relevant and significant than ever before. Parallelly, Serverless Integration has gained popularity, as it helps agile organizations to build integration solutions quickly without having to worry about infrastructure costs. With Microsoft Azure’s serverless offerings, such as Logic Apps, Azure Functions, API Management, Azure Event Grid and Service Bus, organizations can build powerful, secure, and scalable integration solutions with ease. The primary objective of this book is to help you to understand various serverless offerings included within Azure Integration Services, taking you through the basics and industry practices and patterns. This book starts by explaining the concepts of services such as Azure Functions, Logic Apps, and Service Bus with hands-on examples and use cases. After getting to grips with the basics, you will be introduced to API Management and building B2B solutions using Logic Apps Enterprise Integration Pack. This book will help readers to understand building hybrid integration solutions and touches upon Microsoft Cognitive Services and leveraging them in modern integration solutions. Industry practices and patterns are brought to light at appropriate opportunities while explaining various concepts. What you will learn * Learn about the design principles of Microsoft Azure Serverless Integration * Get insights into Azure Functions, Logic Apps, Azure Event Grid and Service Bus * Secure and manage your integration endpoints using Azure API Management * Build advanced B2B solutions using Logic Apps, Enterprise Integration Pack * Monitor integration solutions using tools available on the market * Discover design patterns for hybrid integration Who this book is for Serverless Integration Design Patterns with Azure is for you if you are a solution architect or integration professional aiming to build complex cloud solutions for your organization. Developers looking to build next-level hybrid or cloud solutions will also find this book useful. Prior programming knowledge is necessary.

Designing and deploying solutions using the SAP BusinessObjects Business Intelligence platform 4.2. Key Features * Get up and running with the SAP BusinessObjects Business Intelligence platform * Perform effective data analysis and visualization for actionable insights * Enhance your BI strategy by creating different types of reports and dashboards using SAP BusinessObjects Book Description The SAP BusinessObjects Business Intelligence platform is a powerful reporting and analysis tool. This book is the ideal introduction to the SAP BusinessObjects Business Intelligence platform, introducing you to its data visualization, visual analytics, reporting, and dashboarding capabilities. The book starts with an overview of the BI platform and various data sources for reporting. Then, we move on to looking at data visualization, analysis, reporting, and analytics using BusinessObjects Business Intelligence tools. You will learn about the features associated with reporting, scheduling, and distribution and learn how to deploy the platform. Toward the end, you will learn about the strategies and factors that should be considered during deployment. By the end, you will be confident working with the SAP BusinessObjects Business Intelligence platform to deliver better insights for more effective decision making. What you will learn * Work with various tools to create interactive data visualization and analysis * Query, report, and analyze with SAP Business Objects Web Intelligence * Create a report in SAP Crystal Reports for Enterprise * Visualize and manipulate data using an SAP Lumira Storyboard * Deep dive into the workings of the SAP predictive analytics tool * Deploy and configure SAP BO Intelligence platform 4.2 Who this book is for This book is for Business Intelligence professionals and existing SAP ecosystem users who want to perform effective Business Intelligence using SAP BusinessObjects.

Convert Android to a powerful pentesting platform. Key Features * Get up and running with Kali Linux NetHunter * Connect your Android device and gain full control over Windows, OSX, or Linux devices * Crack Wi-Fi passwords and gain access to devices connected over the same network collecting intellectual data Book Description Kali NetHunter is a version of the popular and powerful Kali Linux pentesting platform, designed to be installed on mobile devices. Hands-On Penetration Testing with Kali NetHunter will teach you the components of NetHunter and how to install the software. You’ll also learn about the different tools included and how to optimize and use a package, obtain desired results, perform tests, and make your environment more secure. Starting with an introduction to Kali NetHunter, you will delve into different phases of the pentesting process. This book will show you how to build your penetration testing environment and set up your lab. You will gain insight into gathering intellectual data, exploiting vulnerable areas, and gaining control over target systems. As you progress through the book, you will explore the NetHunter tools available for exploiting wired and wireless devices. You will work through new ways to deploy existing tools designed to reduce the chances of detection. In the concluding chapters, you will discover tips and best practices for integrating security hardening into your Android ecosystem. By the end of this book, you will have learned to successfully use a mobile penetration testing device based on Kali NetHunter and Android to accomplish the same tasks you would traditionally, but in a smaller and more mobile form factor. What you will learn * Choose and configure a hardware device to use Kali NetHunter * Use various tools during pentests * Understand NetHunter suite components * Discover tips to effectively use a compact mobile platform * Create your own Kali NetHunter-enabled device and configure it for optimal results * Learn to scan and gather information from a target * Explore hardware adapters for testing and auditing wireless networks and Bluetooth devices Who this book is for Hands-On Penetration Testing with Kali NetHunter is for pentesters, ethical hackers, and security professionals who want to learn to use Kali NetHunter for complete mobile penetration testing and are interested in venturing into the mobile domain. Some prior understanding of networking assessment and Kali Linux will be helpful.

Leverage the power of reward-based training for your deep learning models with Python Key Features * Understand Q-learning algorithms to train neural networks using Markov Decision Process (MDP) * Study practical deep reinforcement learning using Q-Networks * Explore state-based unsupervised learning for machine learning models Book Description Q-learning is a machine learning algorithm used to solve optimization problems in artificial intelligence (AI). It is one of the most popular fields of study among AI researchers. This book starts off by introducing you to reinforcement learning and Q-learning, in addition to helping you get familiar with OpenAI Gym as well as libraries such as Keras and TensorFlow. A few chapters into the book, you will gain insights into modelfree Q-learning and use deep Q-networks and double deep Q-networks to solve complex problems. This book will guide you in exploring use cases such as self-driving vehicles and OpenAI Gym’s CartPole problem. You will also learn how to tune and optimize Q-networks and their hyperparameters. As you progress, you will understand the reinforcement learning approach to solving real-world problems. You will also explore how to use Q-learning and related algorithms in real-world applications such as scientific research. Toward the end, you’ll gain a sense of what’s in store for reinforcement learning. By the end of this book, you will be equipped with the skills you need to solve reinforcement learning problems using Q-learning algorithms with OpenAI Gym, Keras, and TensorFlow. What you will learn * Explore the fundamentals of reinforcement learning and the state-action-reward process * Understand Markov decision processes * Get well versed with libraries such as Keras, and TensorFlow * Create and deploy model-free learning and deep Q-learning agents with TensorFlow, Keras, and OpenAI Gym * Choose and optimize a Q-Network’s learning parameters and fine-tune its performance * Discover real-world applications and use cases of Q-learning Who this book is for If you are a machine learning developer, engineer, or professional who wants to delve into the deep learning approach for a complex environment, then this is the book for you. Proficiency in Python programming and basic understanding of decision-making in reinforcement learning is assumed.

Explore the exciting world of machine learning with the fastest growing technology in the world Key Features * Understand various machine learning concepts with real-world examples * Implement a supervised machine learning pipeline from data ingestion to validation * Gain insights into how you can use machine learning in everyday life Book Description Machine learning—the ability of a machine to give right answers based on input data—has revolutionized the way we do business. Applied Supervised Learning with Python provides a rich understanding of how you can apply machine learning techniques in your data science projects using Python. You'll explore Jupyter Notebooks, the technology used commonly in academic and commercial circles with in-line code running support. With the help of fun examples, you'll gain experience working on the Python machine learning toolkit—from performing basic data cleaning and processing to working with a range of regression and classification algorithms. Once you’ve grasped the basics, you'll learn how to build and train your own models using advanced techniques such as decision trees, ensemble modeling, validation, and error metrics. You'll also learn data visualization techniques using powerful Python libraries such as Matplotlib and Seaborn. This book also covers ensemble modeling and random forest classifiers along with other methods for combining results from multiple models, and concludes by delving into cross-validation to test your algorithm and check how well the model works on unseen data. By the end of this book, you'll be equipped to not only work with machine learning algorithms, but also be able to create some of your own! What you will learn * Understand the concept of supervised learning and its applications * Implement common supervised learning algorithms using machine learning Python libraries * Validate models using the k-fold technique * Build your models with decision trees to get results effortlessly * Use ensemble modeling techniques to improve the performance of your model * Apply a variety of metrics to compare machine learning models Who this book is for Applied Supervised Learning with Python is for you if you want to gain a solid understanding of machine learning using Python. It'll help if you to have some experience in any functional or object-oriented language and a basic understanding of Python libraries and expressions, such as arrays and dictionaries.

Explore Qt framework and APIs for building cross-platform applications for mobile devices, embedded systems, and IoT Key Features * Build cross-platform applications and deploy them across mobile and connected devices * Design 2D and 3D UIs for embedded systems using Yocto and Qt Creator * Build machine to machine automation solution using QtSensors, QtMQTT, and QtWebSockets Book Description Qt is a world-class framework, helping you to develop rich graphical user interfaces (GUIs) and multi-platform applications that run on all major desktop platforms and most mobile or embedded platforms. The framework helps you connect the dots across platforms and between online and physical experience. This book will help you leverage the fully-featured Qt framework and its modular cross-platform library classes and intuitive APIs to develop applications for mobile, IoT, and industrial embedded systems. Considerations such as screen size, device orientation changes, and small memory will be discussed. We will focus on various core aspects of embedded and mobile systems, such as connectivity, networking, and sensors; there is no IoT without sensors. You will learn how to quickly design a flexible, fast, and responsive UI that looks great. Going further, you will implement different elements in a matter of minutes and synchronize the UI elements with the 3D assets with high precision. You will learn how to create high-performance embedded systems with 3D/2D user interfaces, and deploy and test on your target hardware. The book will explore several new features, including Qt for WebAssembly. At the end of this book, you will learn about creating a full software stack for embedded Linux systems using Yocto and Boot to Qt for Device Creation. What you will learn * Explore the latest features of Qt, such as preview for Qt for Python and Qt for WebAssembly * Create fluid UIs with a dynamic layout for different sized screens * Deploy embedded applications on Linux systems using Yocto * Design Qt APIs for building applications for embedded and mobile devices * Utilize connectivity for networked and machine automated applications * Discover effective techniques to apply graphical effects using Qt Quick apps Who this book is for The book is ideal for mobile developers, embedded systems engineers and enthusiasts who are interested in building cross-platform applications with Qt. Prior knowledge of C++ is required.

Create end-to-end systems that can power robots with artificial vision and deep learning techniques Key Features * Study ROS, the main development framework for robotics, in detail * Learn all about convolutional neural networks, recurrent neural networks, and robotics * Create a chatbot to interact with the robot Book Description Artificial Vision and Language Processing for Robotics begins by discussing the theory behind robots. You'll compare different methods used to work with robots and explore computer vision, its algorithms, and limits. You'll then learn how to control the robot with natural language processing commands. You'll study Word2Vec and GloVe embedding techniques, non-numeric data, recurrent neural network (RNNs), and their advanced models. You'll create a simple Word2Vec model with Keras, as well as build a convolutional neural network (CNN) and improve it with data augmentation and transfer learning. You'll study the ROS and build a conversational agent to manage your robot. You'll also integrate your agent with the ROS and convert an image to text and text to speech. You'll learn to build an object recognition system using a video. By the end of this book, you'll have the skills you need to build a functional application that can integrate with a ROS to extract useful information about your environment. What you will learn * Explore the ROS and build a basic robotic system * Understand the architecture of neural networks * Identify conversation intents with NLP techniques * Learn and use the embedding with Word2Vec and GloVe * Build a basic CNN and improve it using generative models * Use deep learning to implement artificial intelligence(AI)and object recognition * Develop a simple object recognition system using CNNs * Integrate AI with ROS to enable your robot to recognize objects Who this book is for Artificial Vision and Language Processing for Robotics is for robotics engineers who want to learn how to integrate computer vision and deep learning techniques to create complete robotic systems. It will prove beneficial to you if you have working knowledge of Python and a background in deep learning. Knowledge of the ROS is a plus.

Work with the powerful subscription software, Office 365 to increase your organization's efficiency by managing file sharing, email exchange and much more. Key Features * Become well versed with Office 365 and leverage its capabilities for your business * Speed up your workflow and effectively collaborate using Office Web Apps * Learn to set audio and web conferences and seamlessly access your workspace Book Description Microsoft Office 365 combines the popular Office suite with next-generation cloud computing capabilities. With this user guide, you'll be able to implement its software features for effective business communication and collaboration. This book begins by providing you with a quick introduction to the user interface (UI) and the most commonly used features of Office 365. After covering the core aspects of this suite, you'll learn how to perform various email functions via Exchange. Next, you will learn how to communicate using Skype for Business and Microsoft Teams. To boost your productivity, this book will help you learn everything from using instant messaging to conducting audio and web conferences, and even accessing business information from any location. In the final chapters, you will learn to work in a systematic style using file management and collaboration with OneDrive for Business using SharePoint. By the end of this book, you'll be equipped with the knowledge you need to take full advantage of Office 365 and level up your organization's productivity. What you will learn * Understand the UI of Office 365 * Perform a variety of email functions through Exchange * Communicate using Skype for Business and Microsoft Teams * Explore file management using OneDrive for Business * Collaborate using SharePoint * Understand how to leverage Office 365 in your daily tasks Who this book is for If you are an IT professional who wants to upgrade your traditional Office suite, this book is for you. Users looking to learn, configure, manage, and maintain an Office 365 environment in their organization will also find this book useful. Some understanding of Microsoft Office Suite and cloud computing basics will be beneficial.

Solve complex business problems by understanding users better, finding the right problem to solve, and building lean event-driven systems to give your customers what they really want Key Features * Apply DDD principles using modern tools such as EventStorming, Event Sourcing, and CQRS * Learn how DDD applies directly to various architectural styles such as REST, reactive systems, and microservices * Empower teams to work flexibly with improved services and decoupled interactions Book Description Developers across the world are rapidly adopting DDD principles to deliver powerful results when writing software that deals with complex business requirements. This book will guide you in involving business stakeholders when choosing the software you are planning to build for them. By figuring out the temporal nature of behavior-driven domain models, you will be able to build leaner, more agile, and modular systems. You’ll begin by uncovering domain complexity and learn how to capture the behavioral aspects of the domain language. You will then learn about EventStorming and advance to creating a new project in .NET Core 2.1; you’ll also and write some code to transfer your events from sticky notes to C#. The book will show you how to use aggregates to handle commands and produce events. As you progress, you’ll get to grips with Bounded Contexts, Context Map, Event Sourcing, and CQRS. After translating domain models into executable C# code, you will create a frontend for your application using Vue.js. In addition to this, you’ll learn how to refactor your code and cover event versioning and migration essentials. By the end of this DDD book, you will have gained the confidence to implement the DDD approach in your organization and be able to explore new techniques that complement what you’ve learned from the book. What you will learn * Discover and resolve domain complexity together with business stakeholders * Avoid common pitfalls when creating the domain model * Study the concept of Bounded Context and aggregate * Design and build temporal models based on behavior and not only data * Explore benefits and drawbacks of Event Sourcing * Get acquainted with CQRS and to-the-point read models with projections * Practice building one-way flow UI with Vue.js * Understand how a task-based UI conforms to DDD principles Who this book is for This book is for .NET developers who have an intermediate level understanding of C#, and for those who seek to deliver value, not just write code. Intermediate level of competence in JavaScript will be helpful to follow the UI chapters.

Explore practical use cases to learn everything from Linux components, and functionalities, through to hardware and software support Key Features * Gain a clear understanding of how to design a Linux environment * Learn more about the architecture of the modern Linux operating system(OS) * Understand infrastructure needs and design a high-performing computing environment Book Description It is very important to understand the flexibility of an infrastructure when designing an efficient environment. In this book, you will cover everything from Linux components and functionalities through to hardware and software support, which will help you to implement and tune effective Linux-based solutions. This book gets started with an overview of Linux design methodology. Next, you will focus on the core concepts of designing a solution. As you progress, you will gain insights into the kinds of decisions you need to make when deploying a high-performance solution using Gluster File System (GlusterFS). In the next set of chapters, the book will guide you through the technique of using Kubernetes as an orchestrator for deploying and managing containerized applications. In addition to this, you will learn how to apply and configure Kubernetes for your NGINX application. You’ll then learn how to implement an ELK stack, which is composed of Elasticsearch, Logstash, and Kibana. In the concluding chapters, you will focus on installing and configuring a Saltstack solution to manage different Linux distributions, and explore a variety of design best practices. By the end of this book, you will be well-versed with designing a high-performing computing environment for complex applications to run on. By the end of the book, you will have delved inside the most detailed technical conditions of designing a solution, and you will have also dissected every aspect in detail in order to implement and tune open source Linux-based solutions What you will learn * Study the basics of infrastructure design and the steps involved * Expand your current design portfolio with Linux-based solutions * Discover open source software-based solutions to optimize your architecture * Understand the role of high availability and fault tolerance in a resilient design * Identify the role of containers and how they improve your continuous integration and continuous deployment pipelines * Gain insights into optimizing and making resilient and highly available designs by applying industry best practices Who this book is for This intermediate-level book is for Linux system administrators, Linux support engineers, DevOps engineers, Linux consultants or any open source technology professional looking to learn or expand their knowledge in architecting, designing and implementing solutions based on Linux and open source software. Prior experience in Linux is required.

Master scala's advanced techniques to solve real-world problems in data analysis and gain valuable insights from your data Key Features * A beginner's guide for performing data analysis loaded with numerous rich, practical examples * Access to popular Scala libraries such as Breeze, Saddle for efficient data manipulation and exploratory analysis * Develop applications in Scala for real-time analysis and machine learning in Apache Spark Book Description Efficient business decisions with an accurate sense of business data helps in delivering better performance across products and services. This book helps you to leverage the popular Scala libraries and tools for performing core data analysis tasks with ease. The book begins with a quick overview of the building blocks of a standard data analysis process. You will learn to perform basic tasks like Extraction, Staging, Validation, Cleaning, and Shaping of datasets. You will later deep dive into the data exploration and visualization areas of the data analysis life cycle. You will make use of popular Scala libraries like Saddle, Breeze, Vegas, and PredictionIO for processing your datasets. You will learn statistical methods for deriving meaningful insights from data. You will also learn to create applications for Apache Spark 2.x on complex data analysis, in real-time. You will discover traditional machine learning techniques for doing data analysis. Furthermore, you will also be introduced to neural networks and deep learning from a data analysis standpoint. By the end of this book, you will be capable of handling large sets of structured and unstructured data, perform exploratory analysis, and building efficient Scala applications for discovering and delivering insights What you will learn * Techniques to determine the validity and confidence level of data * Apply quartiles and n-tiles to datasets to see how data is distributed into many buckets * Create data pipelines that combine multiple data lifecycle steps * Use built-in features to gain a deeper understanding of the data * Apply Lasso regression analysis method to your data * Compare Apache Spark API with traditional Apache Spark data analysis Who this book is for If you are a data scientist or a data analyst who wants to learn how to perform data analysis using Scala, this book is for you. All you need is knowledge of the basic fundamentals of Scala programming.