Discover the unified, distributed storage system and improve the performance of applications Key Features * Explore the latest features of Ceph's Mimic release * Get to grips with advanced disaster and recovery practices for your storage * Harness the power of Reliable Autonomic Distributed Object Store (RADOS) to help you optimize storage systems Book Description Ceph is an open source distributed storage system that is scalable to Exabyte deployments. This second edition of Mastering Ceph takes you a step closer to becoming an expert on Ceph. You’ll get started by understanding the design goals and planning steps that should be undertaken to ensure successful deployments. In the next sections, you’ll be guided through setting up and deploying the Ceph cluster with the help of orchestration tools. This will allow you to witness Ceph’s scalability, erasure coding (data protective) mechanism, and automated data backup features on multiple servers. You’ll then discover more about the key areas of Ceph including BlueStore, erasure coding and cache tiering with the help of examples. Next, you’ll also learn some of the ways to export Ceph into non-native environments and understand some of the pitfalls that you may encounter. The book features a section on tuning that will take you through the process of optimizing both Ceph and its supporting infrastructure. You’ll also learn to develop applications, which use Librados and distributed computations with shared object classes. Toward the concluding chapters, you’ll learn to troubleshoot issues and handle various scenarios where Ceph is not likely to recover on its own. By the end of this book, you’ll be able to master storage management with Ceph and generate solutions for managing your infrastructure. What you will learn * Plan, design and deploy a Ceph cluster * Get well-versed with different features and storage methods * Carry out regular maintenance and daily operations with ease * Tune Ceph for improved ROI and performance * Recover Ceph from a range of issues * Upgrade clusters to BlueStore Who this book is for If you are a storage professional, system administrator, or cloud engineer looking for guidance on building powerful storage solutions for your cloud and on-premise infrastructure, this book is for you.

An effective guide to designing, building, and deploying enterprise Java microservices with Eclipse MicroProfile Key Features * Create cloud-native microservices with ease using this detailed guide * Avoid vendor lock-in when implementing microservices using Eclipse MicroProfile * Discover why MicroProfile is a great specification for building microservices in multi-cloud environments Book Description Eclipse MicroProfile has gained momentum in the industry as a multi-vendor, interoperable, community-driven specification. It is a major disruptor that allows organizations with large investments in enterprise Java to move to microservices without spending a lot on retraining their workforce. This book is based on MicroProfile 2.2, however, it will guide you in running your applications in MicroProfile 3.0. You'll start by understanding why microservices are important in the digital economy and how MicroProfile addresses the need for enterprise Java microservices. You'll learn about the subprojects that make up a MicroProfile, its value proposition to organizations and developers, and its processes and governance. As you advance, the book takes you through the capabilities and code examples of MicroProfile’s subprojects - Config, Fault Tolerance, Health Check, JWT Propagation, Metrics, and OpenTracing. Finally, you’ll be guided in developing a conference application using Eclipse MicroProfile, and explore possible scenarios of what’s next in MicroProfile with Jakarta EE. By the end of this book, you'll have gained a clear understanding of Eclipse MicroProfile and its role in enterprise Java microservices. What you will learn * Understand why microservices are important in the digital economy * Analyze how MicroProfile addresses the need for enterprise Java microservices * Test and secure your applications with Eclipse MicroProfile * Get to grips with various MicroProfile capabilities such as OpenAPI and Typesafe REST Client * Explore reactive programming with MicroProfile Stream and Messaging candidate APIs * Discover and implement coding best practices using MicroProfile Who this book is for If you’re a Java developer who wants to create enterprise microservices, this book is for you. Familiarity with Java EE and the concept of microservices will help you get the most out of this book.

Learn how to write automated tests for Dynamics 365 Business Central and see how to implement it in your daily work Key Features * Leverage automated testing to advance over traditional manual testing methods * Write, design, and implement automated tests * Explore various testing frameworks and tools compatible with Microsoft Dynamics 365 Business Central Book Description Dynamics 365 Business Central is the new cloud-based SaaS ERP proposition from Microsoft. It’s not as simple as it used to be way back when it was called Navigator, Navision Financials, or Microsoft Business Solutions-Navision. Our development practices are becoming more formal, and with this, the call for test automation is pressing on us. This book will teach you to leverage testing tools available with Dynamics 365 Business Central to perform automated testing. We’ll begin with a quick introduction to automated testing, followed by an overview of test automation in Dynamics 365 Business Central. Then you’ll learn to design and build automated tests and we’ll go through some efficient methods to get from requirements to application and testing code. Lastly, you’ll learn to incorporate your own and Microsoft tests into your daily development practice. By the end of the book, you’ll be able to write your own automated tests for Dynamics 365 Business Central. What you will learn * Understand what automated tests are, and when and why to use them * Explore the five pillars of the Testability Framework of Business Central * Design and write automated tests for Business Central * Make use of standard automated tests and their helper libraries * Integrate automated tests into your development practice Who this book is for This book is for consultants, testers, developers, and development managers working with Microsoft Dynamics NAV and Business Central. Being a book on automated testing techniques, it also caters to both functional and technical development teams.

Get up to speed with various penetration testing techniques and resolve security threats of varying complexity Key Features * Enhance your penetration testing skills to tackle security threats * Learn to gather information, find vulnerabilities, and exploit enterprise defenses * Navigate secured systems with the most up-to-date version of Kali Linux (2019.1) and Metasploit (5.0.0) Book Description Sending information via the internet is not entirely private, as evidenced by the rise in hacking, malware attacks, and security threats. With the help of this book, you'll learn crucial penetration testing techniques to help you evaluate enterprise defenses. You'll start by understanding each stage of pentesting and deploying target virtual machines, including Linux and Windows. Next, the book will guide you through performing intermediate penetration testing in a controlled environment. With the help of practical use cases, you'll also be able to implement your learning in real-world scenarios. By studying everything from setting up your lab, information gathering and password attacks, through to social engineering and post exploitation, you'll be able to successfully overcome security threats. The book will even help you leverage the best tools, such as Kali Linux, Metasploit, Burp Suite, and other open source pentesting tools to perform these techniques. Toward the later chapters, you'll focus on best practices to quickly resolve security threats. By the end of this book, you'll be well versed with various penetration testing techniques so as to be able to tackle security threats effectively What you will learn * Perform entry-level penetration tests by learning various concepts and techniques * Understand both common and not-so-common vulnerabilities from an attacker's perspective * Get familiar with intermediate attack methods that can be used in real-world scenarios * Understand how vulnerabilities are created by developers and how to fix some of them at source code level * Become well versed with basic tools for ethical hacking purposes * Exploit known vulnerable services with tools such as Metasploit Who this book is for If you’re just getting started with penetration testing and want to explore various security domains, this book is for you. Security professionals, network engineers, and amateur ethical hackers will also find this book useful. Prior knowledge of penetration testing and ethical hacking is not necessary.

Learn exploratory data analysis concepts using powerful R packages to enhance your R data analysis skills Key Features * Speed up your data analysis projects using powerful R packages and techniques * Create multiple hands-on data analysis projects using real-world data * Discover and practice graphical exploratory analysis techniques across domains Book Description Hands-On Exploratory Data Analysis with R will help you build not just a foundation but also expertise in the elementary ways to analyze data. You will learn how to understand your data and summarize its main characteristics. You'll also uncover the structure of your data, and you'll learn graphical and numerical techniques using the R language. This book covers the entire exploratory data analysis (EDA) process—data collection, generating statistics, distribution, and invalidating the hypothesis. As you progress through the book, you will learn how to set up a data analysis environment with tools such as ggplot2, knitr, and R Markdown, using tools such as DOE Scatter Plot and SML2010 for multifactor, optimization, and regression data problems. By the end of this book, you will be able to successfully carry out a preliminary investigation on any dataset, identify hidden insights, and present your results in a business context. What you will learn * Learn powerful R techniques to speed up your data analysis projects * Import, clean, and explore data using powerful R packages * Practice graphical exploratory analysis techniques * Create informative data analysis reports using ggplot2 * Identify and clean missing and erroneous data * Explore data analysis techniques to analyze multi-factor datasets Who this book is for Hands-On Exploratory Data Analysis with R is for data enthusiasts who want to build a strong foundation for data analysis. If you are a data analyst, data engineer, software engineer, or product manager, this book will sharpen your skills in the complete workflow of exploratory data analysis.

Understand the constructs of the Python programming language and use them to build data science projects Key Features * Learn the basics of developing applications with Python and deploy your first data application * Take your first steps in Python programming by understanding and using data structures, variables, and loops * Delve into Jupyter, NumPy, Pandas, SciPy, and sklearn to explore the data science ecosystem in Python Book Description Python is the most widely used programming language for building data science applications. Complete with step-by-step instructions, this book contains easy-to-follow tutorials to help you learn Python and develop real-world data science projects. The “secret sauce” of the book is its curated list of topics and solutions, put together using a range of real-world projects, covering initial data collection, data analysis, and production. This Python book starts by taking you through the basics of programming, right from variables and data types to classes and functions. You’ll learn how to write idiomatic code and test and debug it, and discover how you can create packages or use the range of built-in ones. You’ll also be introduced to the extensive ecosystem of Python data science packages, including NumPy, Pandas, scikit-learn, Altair, and Datashader. Furthermore, you’ll be able to perform data analysis, train models, and interpret and communicate the results. Finally, you’ll get to grips with structuring and scheduling scripts using Luigi and sharing your machine learning models with the world as a microservice. By the end of the book, you’ll have learned not only how to implement Python in data science projects, but also how to maintain and design them to meet high programming standards. What you will learn * Code in Python using Jupyter and VS Code * Explore the basics of coding – loops, variables, functions, and classes * Deploy continuous integration with Git, Bash, and DVC * Get to grips with Pandas, NumPy, and scikit-learn * Perform data visualization with Matplotlib, Altair, and Datashader * Create a package out of your code using poetry and test it with PyTest * Make your machine learning model accessible to anyone with the web API Who this book is for If you want to learn Python or data science in a fun and engaging way, this book is for you. You’ll also find this book useful if you’re a high school student, researcher, analyst, or anyone with little or no coding experience with an interest in the subject and courage to learn, fail, and learn from failing. A basic understanding of how computers work will be useful.

Explore the blockchain-based decentralized platform and understand how Ethereum works with Dapps examples Key Features * Explore the Ethereum ecosystem and understand the latest research on the platform * Build decentralized apps (Dapps) using smart contracts and Ethereum with the help of practical examples * Learn to make your decentralized applications fast and highly secure Book Description Ethereum is a blockchain-based, decentralized computing platform that allows running smart contracts. This book provides a basic overview of how Ethereum works, its ecosystem, mining process, and the consensus mechanism. It also demonstrates a step-by-step approach for building decentralized applications. This book begins with the very basics of Blockchain technology. Then it dives deep into the Ethereum architecture, framework and tools in its ecosystem. It also provides you an overview of ongoing research on Ethereum, for example, Layer 1 and 2 scaling solution, Stablecoin, ICO/STO/IEO, etc. Next, it explains Solidity language in detail, and provides step-by-step instructions for designing, developing, testing, deploying, and monitoring decentralized applications. In addition, you’ll learn how to use Truffle, Remix, Infura, Metamask, and many other Ethereum technologies. It’ll also help you develop your own cryptocurrency by creating ERC20, and ERC721 smart contracts from scratch. Finally, we explain private blockchains, and you learn how to interact with smart contracts through wallets. What you will learn * Understand the concepts of blockchain and cryptocurrency * Master Ethereum development tools such as Truffle, Remix IDE and Infura * Delve into smart contract development * Develop DApps frontend using Node.js, React.js, and Web3js API * Learn Etherscan and other tools to secure and monitor smart contracts * Develop and debug smart contracts by working with Remix * Apply Truffle suite to compile, migrate, and unit test smart contracts * Explore smart contracts such as ERC20 token and decentralized digital market Who this book is for This book is for all developers and architects who want to explore Ethereum blockchain fundamentals and get started with building real-world decentralized applications. Knowledge of an object-oriented programming language such as JavaScript will be useful but not mandatory.

Explore modern game programming and rendering techniques to build games using C++ programming language and its popular libraries Key Features * Learn how you can build basic 2D and complex 3D games with C++ * Understand shadows, texturing, lighting, and rendering in 3D game development using OpenGL * Uncover modern graphics programming techniques and GPU compute methods using the Vulkan API Book Description Although numerous languages are currently being used to develop games, C++ remains the standard for fabricating expert libraries and tool chains for game development. This book introduces you to the world of game development with C++. C++ Game Development By Example starts by touching upon the basic concepts of math, programming, and computer graphics and creating a simple side-scrolling action 2D game. You'll build a solid foundation by studying basic game concepts such as creating game loops, rendering 2D game scenes using SFML, 2D sprite creation and animation, and collision detection. The book will help you advance to creating a 3D physics puzzle game using modern OpenGL and the Bullet physics engine. You'll understand the graphics pipeline, which entails creating 3D objects using vertex and index buffers and rendering them to the scene using vertex and fragment shaders. Finally, you'll create a basic project using the Vulkan library that'll help you get to grips with creating swap chains, image views, render passes, and frame buffers for building high-performance graphics in your games. By the end of this book, you’ll be ready with 3 compelling projects created with SFML, the Vulkan API, and OpenGL, and you'll be able take your game and graphics programming skills to the next level. What you will learn * Understand shaders and how to write a basic vertex and fragment shader * Build a Visual Studio project and add SFML to it * Discover how to create sprite animations and a game character class * Add sound effects and background music to your game * Grasp how to integrate Vulkan into Visual Studio * Create shaders and convert them to the SPIR-V binary format Who this book is for If you’re a developer keen to learn game development with C++ or get up to date with game development, this book is for you. Some knowledge of C++ programming is assumed.

Build efficient forecasting models using traditional time series models and machine learning algorithms. Key Features * Perform time series analysis and forecasting using R packages such as Forecast and h2o * Develop models and find patterns to create visualizations using the TSstudio and plotly packages * Master statistics and implement time-series methods using examples mentioned Book Description Time series analysis is the art of extracting meaningful insights from, and revealing patterns in, time series data using statistical and data visualization approaches. These insights and patterns can then be utilized to explore past events and forecast future values in the series. This book explores the basics of time series analysis with R and lays the foundations you need to build forecasting models. You will learn how to preprocess raw time series data and clean and manipulate data with packages such as stats, lubridate, xts, and zoo. You will analyze data and extract meaningful information from it using both descriptive statistics and rich data visualization tools in R such as the TSstudio, plotly, and ggplot2 packages. The later section of the book delves into traditional forecasting models such as time series linear regression, exponential smoothing (Holt, Holt-Winter, and more) and Auto-Regressive Integrated Moving Average (ARIMA) models with the stats and forecast packages. You'll also cover advanced time series regression models with machine learning algorithms such as Random Forest and Gradient Boosting Machine using the h2o package. By the end of this book, you will have the skills needed to explore your data, identify patterns, and build a forecasting model using various traditional and machine learning methods. What you will learn * Visualize time series data and derive better insights * Explore auto-correlation and master statistical techniques * Use time series analysis tools from the stats, TSstudio, and forecast packages * Explore and identify seasonal and correlation patterns * Work with different time series formats in R * Explore time series models such as ARIMA, Holt-Winters, and more * Evaluate high-performance forecasting solutions Who this book is for Hands-On Time Series Analysis with R is ideal for data analysts, data scientists, and all R developers who are looking to perform time series analysis to predict outcomes effectively. A basic knowledge of statistics is required; some knowledge in R is expected, but not mandatory.

Build optimized, efficient, and real-time applications that are production-ready using Unreal Engine's Material Editor Key Features * Create stunning visual effects for 3D games and high-quality graphics * Design efficient Shaders for mobile platforms without sacrificing their realism * Discover what goes into the structure of Shaders and why lighting works the way it does Book Description Unreal Engine 4 is a powerful game engine, one which has seen a recent boost in widespread adoption thanks to its ease of use and the powerful rendering pipeline that it packs. Seeing as how it's relatively easy to create stunning presentations and visuals, Unreal has quickly become a strong contender in industries where this kind of software had been previously denied entry. With that in mind, this book aims to help you get the most out of Unreal Engine 4 - from creating awe-inspiring graphics to delivering optimized experiences to your users. This is possible thanks to a mixture of hands-on experience with real materials and the theory behind them. You will immediately know how to create that material that you want to display, and you'll also end up with the knowledge that will let you know how to control it. All of this will be done without losing sight of two key components of any real-time application - optimization, and efficiency. The materials that you create will be light and efficient, and they will vary depending on your target platform. You'll know which techniques can be used in any kind of device and which ones should be kept to high-end machines, giving you the confidence to tackle any material-related task that you can imagine. Hop onboard and discover how! What you will learn * Master Unreal Engine's rendering pipeline for developing real-time graphics * Use physically based rendering (PBR) for building materials and lighting solutions * Build optimized materials for games targeting multiple platforms * Understand Unreal Engine's node and functions for creating desirable effects * Design and build production-ready shaders * Explore Unreal Engine's Material Editor for building complex materials and textures Who this book is for This book is for developers who want to create their first Shaders in Unreal Engine 4 or wish to take their game to a whole new level by adding professional post-processing effects. A solid understanding of Unreal is required to get the most from this book.

Develop native applications for multiple mobile and desktop platforms including but not limited to iOS, Android, and UWP with the Xamarin framework and Xamarin.Forms Key Features * Understand .NET Core and its cross-platform development philosophy * Build Android, iOS, and Windows mobile applications with C#, .NET Core, and Azure Cloud Services * Bring Artificial Intelligence capabilities into your mobile applications with Azure AI Book Description .NET Core is the general umbrella term used for Microsoft’s cross-platform toolset. Xamarin used for developing mobile applications, is one of the app model implementations for .NET Core infrastructure. In this book, you will learn how to design, architect, and develop highly attractive, maintainable, efficient, and robust mobile applications for multiple platforms, including iOS, Android, and UWP, with the toolset provided by Microsoft using Xamarin, .NET Core, and Azure Cloud Services. This book will take you through various phases of application development with Xamarin, from environment setup, design, and architecture to publishing, using real-world scenarios. Throughout the book, you will learn how to develop mobile apps using Xamarin, Xamarin.Forms and .NET Standard; implement a webbased backend composed of microservices with .NET Core using various Azure services including but not limited to Azure App Services, Azure Active Directory, Notification Hub, Logic Apps, and Azure Functions, Cognitive Services; create data stores using popular database technologies such as Cosmos DB, SQL and Realm. Towards the end, the book will help developers to set up an efficient and maintainable development pipeline to manage the application life cycle using Visual Studio App Center and Visual Studio Services. What you will learn * Implement native applications for multiple mobile and desktop platforms * Understand and use various Azure Services with .NET Core * Make use of architectural patterns designed for mobile and web applications * Understand the basic Cosmos DB concepts * Understand how different app models can be used to create an app service * Explore the Xamarin and Xamarin.Forms UI suite with .NET Core for building mobile applications Who this book is for This book is for mobile developers who wish to develop cross-platform mobile applications. Programming experience with C# is required. Some knowledge and understanding of core elements and cross-platform application development with .NET is required.

Explore supervised machine learning with R by studying popular real-world uses cases such as object detection in driverless cars, customer churn, and default prediction Key Features * Study supervised learning algorithms by using real-world datasets * Fine tune optimal parameters with hyperparameter optimization * Select the best algorithm using the model evaluation framework Book Description R provides excellent visualization features that are essential for exploring data before using it in automated learning. Applied Supervised Learning with R helps you cover the complete process of employing R to develop applications using supervised machine learning algorithms for your business needs. The book starts by helping you develop your analytical thinking to create a problem statement using business inputs and domain research. You will then learn different evaluation metrics that compare various algorithms, and later progress to using these metrics to select the best algorithm for your problem. After finalizing the algorithm you want to use, you will study the hyperparameter optimization technique to fine-tune your set of optimal parameters. To prevent you from overfitting your model, a dedicated section will even demonstrate how you can add various regularization terms. By the end of this book, you will have the advanced skills you need for modeling a supervised machine learning algorithm that precisely fulfills your business needs. What you will learn * Develop analytical thinking to precisely identify a business problem * Wrangle data with dplyr, tidyr, and reshape2 * Visualize data with ggplot2 * Validate your supervised machine learning model using k-fold * Optimize hyperparameters with grid and random search, and Bayesian optimization * Deploy your model on Amazon Web Services (AWS) Lambda with plumber * Improve your model’s performance with feature selection and dimensionality reduction Who this book is for This book is specially designed for novice and intermediate-level data analysts, data scientists, and data engineers who want to explore different methods of supervised machine learning and its various use cases. Some background in statistics, probability, calculus, linear algebra, and programming will help you thoroughly understand and follow the content of this book.

Understand Gang of Four, architectural, functional, and reactive design patterns and how to implement them on modern Java platforms, such as Java 12 and beyond Key Features * Learn OOP, functional, and reactive patterns for creating readable and maintainable code * Explore architectural patterns and practices for building scalable and reliable applications * Tackle all kinds of performance-related issues and streamline development using design patterns Book Description Java design patterns are reusable and proven solutions to software design problems. This book covers over 60 battle-tested design patterns used by developers to create functional, reusable, and flexible software. Hands-On Design Patterns with Java starts with an introduction to the Unified Modeling Language (UML), and delves into class and object diagrams with the help of detailed examples. You'll study concepts and approaches to object-oriented programming (OOP) and OOP design patterns to build robust applications. As you advance, you'll explore the categories of GOF design patterns, such as behavioral, creational, and structural, that help you improve code readability and enable large-scale reuse of software. You’ll also discover how to work effectively with microservices and serverless architectures by using cloud design patterns, each of which is thoroughly explained and accompanied by real-world programming solutions. By the end of the book, you’ll be able to speed up your software development process using the right design patterns, and you’ll be comfortable working on scalable and maintainable projects of any size. What you will learn * Understand the significance of design patterns for software engineering * Visualize software design with UML diagrams * Strengthen your understanding of OOP to create reusable software systems * Discover GOF design patterns to develop scalable applications * Examine programming challenges and the design patterns that solve them * Explore architectural patterns for microservices and cloud development Who this book is for If you are a developer who wants to learn how to write clear, concise, and effective code for building production-ready applications, this book is for you. Familiarity with the fundamentals of Java is assumed.

Perform cloud-based machine learning and deep learning using Amazon Web Services such as SageMaker, Lex, Comprehend, Translate, and Polly Key Features * Explore popular machine learning and deep learning services with their underlying algorithms * Discover readily available artificial intelligence(AI) APIs on AWS like Vision and Language Services * Design robust architectures to enable experimentation, extensibility, and maintainability of AI apps Book Description From data wrangling through to translating text, you can accomplish this and more with the artificial intelligence and machine learning services available on AWS. With this book, you’ll work through hands-on exercises and learn to use these services to solve real-world problems. You’ll even design, develop, monitor, and maintain machine and deep learning models on AWS. The book starts with an introduction to AI and its applications in different industries, along with an overview of AWS artificial intelligence and machine learning services. You’ll then get to grips with detecting and translating text with Amazon Rekognition and Amazon Translate. The book will assist you in performing speech-to-text with Amazon Transcribe and Amazon Polly. Later, you’ll discover the use of Amazon Comprehend for extracting information from text, and Amazon Lex for building voice chatbots. You will also understand the key capabilities of Amazon SageMaker such as wrangling big data, discovering topics in text collections, and classifying images. Finally, you’ll cover sales forecasting with deep learning and autoregression, before exploring the importance of a feedback loop in machine learning. By the end of this book, you will have the skills you need to implement AI in AWS through hands-on exercises that cover all aspects of the ML model life cycle. What you will learn * Gain useful insights into different machine and deep learning models * Build and deploy robust deep learning systems to production * Train machine and deep learning models with diverse infrastructure specifications * Scale AI apps without dealing with the complexity of managing the underlying infrastructure * Monitor and Manage AI experiments efficiently * Create AI apps using AWS pre-trained AI services Who this book is for This book is for data scientists, machine learning developers, deep learning researchers, and artificial intelligence enthusiasts who want to harness the power of AWS to implement powerful artificial intelligence solutions. A basic understanding of machine learning concepts is expected.

Grasp machine learning concepts, techniques, and algorithms with the help of real-world examples using Python libraries such as TensorFlow and scikit-learn Key Features * Exploit the power of Python to explore the world of data mining and data analytics * Discover machine learning algorithms to solve complex challenges faced by data scientists today * Use Python libraries such as TensorFlow and Keras to create smart cognitive actions for your projects Book Description The surge in interest in machine learning (ML) is due to the fact that it revolutionizes automation by learning patterns in data and using them to make predictions and decisions. If you’re interested in ML, this book will serve as your entry point to ML. Python Machine Learning By Example begins with an introduction to important ML concepts and implementations using Python libraries. Each chapter of the book walks you through an industry adopted application. You’ll implement ML techniques in areas such as exploratory data analysis, feature engineering, and natural language processing (NLP) in a clear and easy-to-follow way. With the help of this extended and updated edition, you’ll understand how to tackle data-driven problems and implement your solutions with the powerful yet simple Python language and popular Python packages and tools such as TensorFlow, scikit-learn, gensim, and Keras. To aid your understanding of popular ML algorithms, the book covers interesting and easy-to-follow examples such as news topic modeling and classification, spam email detection, stock price forecasting, and more. By the end of the book, you’ll have put together a broad picture of the ML ecosystem and will be well-versed with the best practices of applying ML techniques to make the most out of new opportunities. What you will learn * Understand the important concepts in machine learning and data science * Use Python to explore the world of data mining and analytics * Scale up model training using varied data complexities with Apache Spark * Delve deep into text and NLP using Python libraries such NLTK and gensim * Select and build an ML model and evaluate and optimize its performance * Implement ML algorithms from scratch in Python, TensorFlow, and scikit-learn Who this book is for If you’re a machine learning aspirant, data analyst, or data engineer highly passionate about machine learning and want to begin working on ML assignments, this book is for you. Prior knowledge of Python coding is assumed and basic familiarity with statistical concepts will be beneficial although not necessary.

Design clever algorithms that discover hidden patterns and draw responses from unstructured, unlabeled data. Key Features * Build state-of-the-art algorithms that can solve your business' problems * Learn how to find hidden patterns in your data * Revise key concepts with hands-on exercises using real-world datasets Book Description Starting with the basics, Applied Unsupervised Learning with R explains clustering methods, distribution analysis, data encoders, and features of R that enable you to understand your data better and get answers to your most pressing business questions. This book begins with the most important and commonly used method for unsupervised learning - clustering - and explains the three main clustering algorithms - k-means, divisive, and agglomerative. Following this, you'll study market basket analysis, kernel density estimation, principal component analysis, and anomaly detection. You'll be introduced to these methods using code written in R, with further instructions on how to work with, edit, and improve R code. To help you gain a practical understanding, the book also features useful tips on applying these methods to real business problems, including market segmentation and fraud detection. By working through interesting activities, you'll explore data encoders and latent variable models. By the end of this book, you will have a better understanding of different anomaly detection methods, such as outlier detection, Mahalanobis distances, and contextual and collective anomaly detection. What you will learn * Implement clustering methods such as k-means, agglomerative, and divisive * Write code in R to analyze market segmentation and consumer behavior * Estimate distribution and probabilities of different outcomes * Implement dimension reduction using principal component analysis * Apply anomaly detection methods to identify fraud * Design algorithms with R and learn how to edit or improve code Who this book is for Applied Unsupervised Learning with R is designed for business professionals who want to learn about methods to understand their data better, and developers who have an interest in unsupervised learning. Although the book is for beginners, it will be beneficial to have some basic, beginner-level familiarity with R. This includes an understanding of how to open the R console, how to read data, and how to create a loop. To easily understand the concepts of this book, you should also know basic mathematical concepts, including exponents, square roots, means, and medians.

Get up to speed with creational, structural, behavioral and concurrent patterns in Delphi to write clear, concise and effective code Key Features * Delve into the core patterns and components of Delphi in order to master your application's design * Brush up on tricks, techniques, and best practices to solve common design and architectural challenges * Choose the right patterns to improve your program’s efficiency and productivity Book Description Design patterns have proven to be the go-to solution for many common programming scenarios. This book focuses on design patterns applied to the Delphi language. The book will provide you with insights into the language and its capabilities of a runtime library. You'll start by exploring a variety of design patterns and understanding them through real-world examples. This will entail a short explanation of the concept of design patterns and the original set of the 'Gang of Four' patterns, which will help you in structuring your designs efficiently. Next, you'll cover the most important 'anti-patterns' (essentially bad software development practices) to aid you in steering clear of problems during programming. You'll then learn about the eight most important patterns for each creational, structural, and behavioral type. After this, you'll be introduced to the concept of 'concurrency' patterns, which are design patterns specifically related to multithreading and parallel computation. These will enable you to develop and improve an interface between items and harmonize shared memories within threads. Toward the concluding chapters, you'll explore design patterns specific to program design and other categories of patterns that do not fall under the 'design' umbrella. By the end of this book, you'll be able to address common design problems encountered while developing applications and feel confident while building scalable projects. What you will learn * Gain insights into the concept of design patterns * Study modern programming techniques with Delphi * Keep up to date with the latest additions and program design techniques in Delphi * Get to grips with various modern multithreading approaches * Discover creational, structural, behavioral, and concurrent patterns * Determine how to break a design problem down into its component parts Who this book is for Hands-On Design Patterns with Delphi is aimed at beginner-level Delphi developers who want to build scalable and robust applications. Basic knowledge of Delphi is a must.

Unreal Engine 4 for virtual reality game design, development, User Experience design techniques and Blueprint programming to create virtual reality gameplay for HTC Vive, Oculus Rift, PSVR, and Windows Mixed Reality headsets. Key Features * Build VR games from scratch with the power of Unreal Engine 4 * Learn User Experience design practices to take your VR game to the next level * Understand the best practices to creating art for games on HTC Vive, Oculus Rift, and PSVR Book Description With the ability to put players directly in the game, virtual reality gives users the chance to experience digital worlds directly. Nevertheless, many designers are unsure where to start when working with this amazing technology. With this book, you will learn user experience design processes and create immersive gameplay experiences designed for entertainment and player comfort. Using the power of Unreal Engine 4’s Blueprint visual scripting language, you will build player interaction and locomotion systems from scratch and use these flexible systems to create a sample game, as well as develop functional 2D and 3D user interfaces for players to interact with. And also learn the best practices for creating game art for virtual reality. Finally, you will learn how to test your application with your target audience and finalize your game for distribution. By the end of this book, you will have the knowledge to be able to make the leap from traditional game development to creating immersive virtual reality experiences using Unreal Engine 4. What you will learn * Understand how to get started with VR development in Unreal Engine 4 * Design and create interaction and locomotion systems from scratch * Plan and program a sample game for VR * Understand how VR affects user experience and user interfaces * Discuss what is needed to create optimized art for VR * Test your game with users and prepare for distribution Who this book is for The audience for this book is intermediate or advanced users of Unreal Engine 4 but who have not begun working with VR technology. These users are familiar with the game engine and have an interest in VR technology. They are just beginning to explore the VR features that the game engine has to offer.

Grasp advanced PowerShell Core 6.0 functionalities to automate your environment Key Features * Keep up with changes introduced in PowerShell Core 6.0 * Easily maintain appropriate compatibility with older versions * Automate complex tasks, manipulate data, and secure your environment with PowerShell Core 6.0 Book Description PowerShell scripts offer a handy way to automate various chores, however working effectively with these scripts can be a difficult task. This comprehensive guide starts with the fundamentals before moving on to advanced-level topics to help you become a PowerShell Core 6.0 expert. The first module, PowerShell Core 6.0 Fundamentals, begins with the new features of PowerShell Core 6.0, installing it on Linux, and working with parameters, objects and .NET classes from within PowerShell Core 6.0. As you make your way through the chapters, you'll see how to efficiently manage large amounts of data and interact with other services using PowerShell Core 6.0. You'll be able to make the most of PowerShell Core 6.0's powerful automation feature, where you will have different methods available to parse data and manipulate regular expressions and Windows Management Instrumentation (WMI). After having explored automation, you will enter the extending PowerShell Core 6.0 module, covering asynchronous processing and desired state configuration. In the last module, you will learn to extend PowerShell Core 6.0 using advanced scripts and filters, and also debug issues along with working on error handling techniques. By the end of this book, you will be an expert in scripting with PowerShell Core 6.0. What you will learn * Optimize code through the use of functions, switches, and looping structures * Work with objects and operators to test and manipulate data * Parse and manipulate different data types * Create scripts and functions using PowerShell * Use jobs, events, and popular public modules which assist with implementing multithreading * Write .NET classes with ease within the PowerShell * Create and implement regular expressions in PowerShell scripts * Make use of advanced techniques to define and restrict the behavior of parameters Who this book is for If you are a system administrator who wants to become an expert in controlling and automating your Windows environment, then Mastering Windows PowerShell Scripting is for you. It is also ideal for those new to the PowerShell language.

Discover the skill-sets required to implement various approaches to Machine Learning with Python Key Features * Explore unsupervised learning with clustering, autoencoders, restricted Boltzmann machines, and more * Build your own neural network models using modern Python libraries * Practical examples show you how to implement different machine learning and deep learning techniques Book Description Unsupervised learning is about making use of raw, untagged data and applying learning algorithms to it to help a machine predict its outcome. With this book, you will explore the concept of unsupervised learning to cluster large sets of data and analyze them repeatedly until the desired outcome is found using Python. This book starts with the key differences between supervised, unsupervised, and semi-supervised learning. You will be introduced to the best-used libraries and frameworks from the Python ecosystem and address unsupervised learning in both the machine learning and deep learning domains. You will explore various algorithms, techniques that are used to implement unsupervised learning in real-world use cases. You will learn a variety of unsupervised learning approaches, including randomized optimization, clustering, feature selection and transformation, and information theory. You will get hands-on experience with how neural networks can be employed in unsupervised scenarios. You will also explore the steps involved in building and training a GAN in order to process images. By the end of this book, you will have learned the art of unsupervised learning for different real-world challenges. What you will learn * Use cluster algorithms to identify and optimize natural groups of data * Explore advanced non-linear and hierarchical clustering in action * Soft label assignments for fuzzy c-means and Gaussian mixture models * Detect anomalies through density estimation * Perform principal component analysis using neural network models * Create unsupervised models using GANs Who this book is for This book is intended for statisticians, data scientists, machine learning developers, and deep learning practitioners who want to build smart applications by implementing key building block unsupervised learning, and master all the new techniques and algorithms offered in machine learning and deep learning using real-world examples. Some prior knowledge of machine learning concepts and statistics is desirable.

Master the TypeScript language and its latest features. Explore modern application frameworks and utilize industry best practices in TDD, OOP and UI Design. Key Features * Learn the key features of TypeScript 3 and explore advanced language features through in-depth discussions. * Use TypeScript with modern frameworks including Backbone, Angular, Aurelia, React, and Node. * Explore TDD practices, OOP techniques, and industry best practices to create high-quality, modular, and adaptable applications. Book Description TypeScript is both a language and a set of tools to generate JavaScript. It was designed by Anders Hejlsberg at Microsoft to help developers write enterprise-scale JavaScript. Starting with an introduction to the TypeScript language, before moving on to basic concepts, each section builds on previous knowledge in an incremental and easy-to-understand way. Advanced and powerful language features are all covered, including asynchronous programming techniques, decorators, and generics. This book explores many modern JavaScript and TypeScript frameworks side by side in order for the reader to learn their respective strengths and weaknesses. It will also thoroughly explore unit and integration testing for each framework. Best-of-breed applications utilize well-known design patterns in order to be scalable, maintainable, and testable. This book explores some of these object-oriented techniques and patterns, and shows real-world implementations. By the end of the book, you will have built a comprehensive, end-to-end web application to show how TypeScript language features, design patterns, and industry best practices can be brought together in a real-world scenario. What you will learn * Gain insights into core and advanced TypeScript language features * Integrate existing JavaScript libraries and third-party frameworks using declaration files * Target popular JavaScript frameworks, such as Angular, React, and more * Create test suites for your application with Jasmine and Selenium * Organize your application code using modules, AMD loaders, and SystemJS * Explore advanced object-oriented design principles * Compare the various MVC implementations in Aurelia, Angular, React, and more Who this book is for This guide to the TypeScript that starts with basic concepts, and then builds on this knowledge to introduce more advanced language features and frameworks. No prior knowledge of JavaScript is required, although some prior programming experience is assumed. If you are keen to learn TypeScript, this book will give you all of the necessary knowledge and skills to tackle any TypeScript project. If you are already an experienced JavaScript or TypeScript developer, then this book will take your skills to the next level. Learn how to use TypeScript with a multitude of modern frameworks, and choose the best framework for your project requirements. Investigate techniques for Test Driven Development, explore industry-standard design patterns, and learn how to put together a full production-ready TypeScript application.