Over 90 recipes to help you write clean code, solve common JavaScript problems, and work on popular use cases like SPAs, microservices, native mobile development with Node, React, React Native and Electron. Key Features *Over 90 practical recipes to help you write clean and maintainable JavaScript codes with the latest ES8 *Leverage the power of leading web frameworks like Node and React to build modern web apps *Features comprehensive coverage of tools and techniques needed to create multi-platform apps with JavaScript Book Description JavaScript has evolved into a language that you can use on any platform. Modern JavaScript Web Development Cookbook is a perfect blend of solutions for traditional JavaScript development and modern areas that developers have lately been exploring with JavaScript. This comprehensive guide teaches you how to work with JavaScript on servers, browsers, mobile phones and desktops. You will start by exploring the new features of ES8. You will then move on to learning the use of ES8 on servers (with Node.js), with the objective of producing services and microservices and dealing with authentication and CORS. Once you get accustomed to ES8, you will learn to apply it to browsers using frameworks, such as React and Redux, which interact through Ajax with services. You will then understand the use of a modern framework to develop the UI. In addition to this, development for mobile devices with React Native will walk you through the benefits of creating native apps, both for Android and iOS. Finally, you’ll be able to apply your new-found knowledge of server-side and client-side tools to develop applications with Electron. What you will learn *Use the latest features of ES8 and learn new ways to code with JavaScript *Develop server-side services and microservices with Node.js *Learn to do unit testing and to debug your code *Build client-side web applications using React and Redux *Create native mobile applications for Android and iOS with React Native *Write desktop applications with Electron Who this book is for This book is for developers who want to explore the latest JavaScript features, frameworks, and tools for building complete mobile, desktop and web apps, including server and client-side code. You are expected to have working knowledge of JavaScript to get the most out of this book.

Implement machine learning algorithms to build ensemble models using Keras, H2O, Scikit-Learn, Pandas and more Key Features * Apply popular machine learning algorithms using a recipe-based approach * Implement boosting, bagging, and stacking ensemble methods to improve machine learning models * Discover real-world ensemble applications and encounter complex challenges in Kaggle competitions Book Description Ensemble modeling is an approach used to improve the performance of machine learning models. It combines two or more similar or dissimilar machine learning algorithms to deliver superior intellectual powers. This book will help you to implement popular machine learning algorithms to cover different paradigms of ensemble machine learning such as boosting, bagging, and stacking. The Ensemble Machine Learning Cookbook will start by getting you acquainted with the basics of ensemble techniques and exploratory data analysis. You'll then learn to implement tasks related to statistical and machine learning algorithms to understand the ensemble of multiple heterogeneous algorithms. It will also ensure that you don't miss out on key topics, such as like resampling methods. As you progress, you’ll get a better understanding of bagging, boosting, stacking, and working with the Random Forest algorithm using real-world examples. The book will highlight how these ensemble methods use multiple models to improve machine learning results, as compared to a single model. In the concluding chapters, you'll delve into advanced ensemble models using neural networks, natural language processing, and more. You’ll also be able to implement models such as fraud detection, text categorization, and sentiment analysis. By the end of this book, you'll be able to harness ensemble techniques and the working mechanisms of machine learning algorithms to build intelligent models using individual recipes. What you will learn * Understand how to use machine learning algorithms for regression and classification problems * Implement ensemble techniques such as averaging, weighted averaging, and max-voting * Get to grips with advanced ensemble methods, such as bootstrapping, bagging, and stacking * Use Random Forest for tasks such as classification and regression * Implement an ensemble of homogeneous and heterogeneous machine learning algorithms * Learn and implement various boosting techniques, such as AdaBoost, Gradient Boosting Machine, and XGBoost Who this book is for This book is designed for data scientists, machine learning developers, and deep learning enthusiasts who want to delve into machine learning algorithms to build powerful ensemble models. Working knowledge of Python programming and basic statistics is a must to help you grasp the concepts in the book.

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.

From learning about the most sought-after design patterns to a comprehensive coverage of architectural patterns and code testing, this book is all you need to write clean, reusable code Key Features *Write clean, reusable and maintainable code, and make the most of the latest Swift version. *Analyze case studies of some of the popular open source projects and give your workflow a huge boost *Choose patterns such as MVP, MVC, and MVVM depending on the application being built Book Description Swift keeps gaining traction not only amongst Apple developers but also as a server-side language. This book demonstrates how to apply design patterns and best practices in real-life situations, whether that's for new or already existing projects. You’ll begin with a quick refresher on Swift, the compiler, the standard library, and the foundation, followed by the Cocoa design patterns – the ones at the core of many cocoa libraries – to follow up with the creational, structural, and behavioral patterns as defined by the GoF. You'll get acquainted with application architecture, as well as the most popular architectural design patterns, such as MVC and MVVM, and learn to use them in the context of Swift. In addition, you’ll walk through dependency injection and functional reactive programming. Special emphasis will be given to techniques to handle concurrency, including callbacks, futures and promises, and reactive programming. These techniques will help you adopt a test-driven approach to your workflow in order to use Swift Package Manager and integrate the framework into the original code base, along with Unit and UI testing. By the end of the book, you'll be able to build applications that are scalable, faster, and easier to maintain. What you will learn *Work efficiently with Foundation and Swift Standard library *Understand the most critical GoF patterns and use them efficiently *Use Swift 4.2 and its unique capabilities (and limitations) to implement and improve GoF patterns *Improve your application architecture and optimize for maintainability and performance *Write efficient and clean concurrent programs using futures and promises, or reactive programming techniques *Use Swift Package Manager to refactor your program into reusable components *Leverage testing and other techniques for writing robust code Who this book is for This book is for intermediate developers who want to apply design patterns with Swift to structure and scale their applications. You are expected to have basic knowledge of iOS and Swift.

A comprehensive guide to Android forensics, from setting up the workstation to analyzing key artifacts Key Features *Get up and running with modern mobile forensic strategies and techniques *Analyze the most popular Android applications using free and open source forensic tools *Learn malware detection and analysis techniques to investigate mobile cybersecurity incidents Book Description Many forensic examiners rely on commercial, push-button tools to retrieve and analyze data, even though there is no tool that does either of these jobs perfectly. Learning Android Forensics will introduce you to the most up-to-date Android platform and its architecture, and provide a high-level overview of what Android forensics entails. You will understand how data is stored on Android devices and how to set up a digital forensic examination environment. As you make your way through the chapters, you will work through various physical and logical techniques to extract data from devices in order to obtain forensic evidence. You will also learn how to recover deleted data and forensically analyze application data with the help of various open source and commercial tools. In the concluding chapters, you will explore malware analysis so that you’ll be able to investigate cybersecurity incidents involving Android malware. By the end of this book, you will have a complete understanding of the Android forensic process, you will have explored open source and commercial forensic tools, and will have basic skills of Android malware identification and analysis. What you will learn *Understand Android OS and architecture *Set up a forensics environment for Android analysis *Perform logical and physical data extractions *Learn to recover deleted data *Explore how to analyze application data *Identify malware on Android devices *Analyze Android malware Who this book is for If you are a forensic analyst or an information security professional wanting to develop your knowledge of Android forensics, then this is the book for you. Some basic knowledge of the Android mobile platform is expected.

Extend your skills with Odoo 12 to build resourceful and open source business applications Key Features *Explore Odoo 12 capabilities to develop business applications *Program business logic and manipulate data to implement specific business rules in your applications *Integrate Python APIs for building customizable and scalable business logic Book Description Odoo is one of the best platforms for open source ERP and CRM. Its latest version, Odoo 12, brings with it new features and updates in Python packages to develop more customizable applications with additional cloud capabilities. The book begins by covering the development essentials for building business applications. You will start your journey by learning how to install and configure Odoo, and then transition from having no specific knowledge of Odoo to being ready for application development. You will develop your first Odoo application and understand topics such as models and views. Odoo 12 Development Essentials will also guide you in using server APIs to add business logic, helping you lay a solid foundation for advanced topics. As you progress through the chapters, you will be equipped to build and customize your applications and explore the new features in Odoo 12, such as cloud integration, to scale your business applications. You will get insights into building business logic and integrating various APIs into your application. By the end of the book, you will be able to build a business application from scratch by using the latest version of Odoo. What you will learn *Manage Odoo server instances *Create a new Odoo application from scratch using the most frequently used elements *Develop new models and use inheritance to extend existing models *Use ORM methods in the Odoo server and from external clients *Create Kanban views using QWeb effectively *Build custom web and website CMS pages *Use external APIs to integrate Odoo with external applications *Add automated tests and techniques to debug module business logic Who this book is for If you are a developer familiar with Python and MVC design and want to build business applications using Odoo, this book is for you.

Create advanced data and integrated solutions using Azure Event Grid, functions, and containers Key Features * Get familiar with the different design patterns available in Microsoft Azure * Develop Azure cloud architecture and a pipeline management system * Get to know the security best practices for your Azure deployment Book Description Over the years, Azure cloud services have grown quickly, and the number of organizations adopting Azure for their cloud services is also gradually increasing. Leading industry giants are finding that Azure fulfills their extensive cloud requirements. Azure for Architects – Second Edition starts with an extensive introduction to major designing and architectural aspects available with Azure. These design patterns focus on different aspects of the cloud, such as high availability, security, and scalability. Gradually, we move on to other aspects, such as ARM template modular design and deployments. This is the age of microservices and serverless is the preferred implementation mechanism for them. This book covers the entire serverless stack available in Azure including Azure Event Grid, Azure Functions, and Azure Logic Apps. New and advance features like durable functions are discussed at length. A complete integration solution using these serverless technologies is also part of the book. A complete chapter discusses all possible options related to containers in Azure including Azure Kubernetes services, Azure Container Instances and Registry, and Web App for Containers. Data management and integration is an integral part of this book that discusses options for implementing OLTP solutions using Azure SQL, Big Data solutions using Azure Data factory and Data Lake Storage, eventing solutions using stream analytics, and Event Hubs. This book will provide insights into Azure governance features such as tagging, RBAC, cost management, and policies. By the end of this book, you will be able to develop a full-?edged Azure cloud solution that is Enterprise class and future-ready. What you will learn * Create an end-to-end integration solution using Azure Serverless Stack * Learn Big Data solutions and OLTP–based applications on Azure * Understand DevOps implementations using Azure DevOps * Architect solutions comprised of multiple resources in Azure * Develop modular ARM templates * Develop Governance on Azure using locks, RBAC, policies, tags and cost * Learn ways to build data solutions on Azure * Understand the various options related to containers including Azure Kubernetes Services Who this book is for If you are Cloud Architects, DevOps Engineers, or developers who want to learn key architectural aspects of the Azure Cloud platform, then this book is for you. Prior basic knowledge of the Azure Cloud platform is good to have.

Design, develop, and deploy innovative forensic solutions using Python Key Features * Discover how to develop Python scripts for effective digital forensic analysis * Master the skills of parsing complex data structures with Python libraries * Solve forensic challenges through the development of practical Python scripts Book Description Digital forensics plays an integral role in solving complex cybercrimes and helping organizations make sense of cybersecurity incidents. This second edition of Learning Python for Forensics illustrates how Python can be used to support these digital investigations and permits the examiner to automate the parsing of forensic artifacts to spend more time examining actionable data. The second edition of Learning Python for Forensics will illustrate how to develop Python scripts using an iterative design. Further, it demonstrates how to leverage the various built-in and community-sourced forensics scripts and libraries available for Python today. This book will help strengthen your analysis skills and efficiency as you creatively solve real-world problems through instruction-based tutorials. By the end of this book, you will build a collection of Python scripts capable of investigating an array of forensic artifacts and master the skills of extracting metadata and parsing complex data structures into actionable reports. Most importantly, you will have developed a foundation upon which to build as you continue to learn Python and enhance your efficacy as an investigator. What you will learn * Learn how to develop Python scripts to solve complex forensic problems * Build scripts using an iterative design * Design code to accommodate present and future hurdles * Leverage built-in and community-sourced libraries * Understand the best practices in forensic programming * Learn how to transform raw data into customized reports and visualizations * Create forensic frameworks to automate analysis of multiple forensic artifacts * Conduct effective and efficient investigations through programmatic processing Who this book is for If you are a forensics student, hobbyist, or professional seeking to increase your understanding in forensics through the use of a programming language, then Learning Python for Forensics is for you. You are not required to have previous experience in programming to learn and master the content within this book. This material, created by forensic professionals, was written with a unique perspective and understanding for examiners who wish to learn programming.

Work on practical computer vision projects covering advanced object detector techniques and modern deep learning and machine learning algorithms Key Features *Learn about the new features that help unlock the full potential of OpenCV 4 *Build face detection applications with a cascade classifier using face landmarks *Create an optical character recognition (OCR) model using deep learning and convolutional neural networks Book Description Mastering OpenCV, now in its third edition, targets computer vision engineers taking their first steps toward mastering OpenCV. Keeping the mathematical formulations to a solid but bare minimum, the book delivers complete projects from ideation to running code, targeting current hot topics in computer vision such as face recognition, landmark detection and pose estimation, and number recognition with deep convolutional networks. You’ll learn from experienced OpenCV experts how to implement computer vision products and projects both in academia and industry in a comfortable package. You’ll get acquainted with API functionality and gain insights into design choices in a complete computer vision project. You’ll also go beyond the basics of computer vision to implement solutions for complex image processing projects. By the end of the book, you will have created various working prototypes with the help of projects in the book and be well versed with the new features of OpenCV4. What you will learn *Build real-world computer vision problems with working OpenCV code samples *Uncover best practices in engineering and maintaining OpenCV projects *Explore algorithmic design approaches for complex computer vision tasks *Work with OpenCV’s most updated API (v4.0.0) through projects *Understand 3D scene reconstruction and Structure from Motion (SfM) *Study camera calibration and overlay AR using the ArUco Module Who this book is for This book is for those who have a basic knowledge of OpenCV and are competent C++ programmers. You need to have an understanding of some of the more theoretical/mathematical concepts, as we move quite quickly throughout the book.

Leverage the features and libraries of Python to administrate your environment efficiently. Key Features * Learn how to solve problems of system administrators and automate routine activities * Learn to handle regular expressions, network administration * Building GUI, web-scraping and database administration including data analytics Book Description Python has evolved over time and extended its features in relation to every possible IT operation. Python is simple to learn, yet has powerful libraries that can be used to build powerful Python scripts for solving real-world problems and automating administrators' routine activities. The objective of this book is to walk through a series of projects that will teach readers Python scripting with each project. This book will initially cover Python installation and quickly revise basic to advanced programming fundamentals. The book will then focus on the development process as a whole, from setup to planning to building different tools. It will include IT administrators' routine activities (text processing, regular expressions, file archiving, and encryption), network administration (socket programming, email handling, the remote controlling of devices using telnet/ssh, and protocols such as SNMP/DHCP), building graphical user interface, working with websites (Apache log file processing, SOAP and REST APIs communication, and web scraping), and database administration (MySQL and similar database data administration, data analytics, and reporting). By the end of this book, you will be able to use the latest features of Python and be able to build powerful tools that will solve challenging, real-world tasks What you will learn * Understand how to install Python and debug Python scripts * Understand and write scripts for automating testing and routine administrative activities * Understand how to write scripts for text processing, encryption, decryption, and archiving * Handle files, such as pdf, excel, csv, and txt files, and generate reports * Write scripts for remote network administration, including handling emails * Build interactive tools using a graphical user interface * Handle Apache log files, SOAP and REST APIs communication * Automate database administration and perform statistical analysis Who this book is for This book would be ideal for users with some basic understanding of Python programming and who are interested in scaling their programming skills to command line scripting and system administration. Prior knowledge of Python would be necessary.

Build efficient and fast Qt applications, target performance problems, and discover solutions to refine your code Key Features * Build efficient and concurrent applications in Qt to create cross-platform applications * Identify performance bottlenecks and apply the correct algorithm to improve application performance * Delve into parallel programming and memory management to optimize your code Book Description Achieving efficient code through performance tuning is one of the key challenges faced by many programmers. This book looks at Qt programming from a performance perspective. You'll explore the performance problems encountered when using the Qt framework and means and ways to resolve them and optimize performance. The book highlights performance improvements and new features released in Qt 5.9, Qt 5.11, and 5.12 (LTE). You'll master general computer performance best practices and tools, which can help you identify the reasons behind low performance, and the most common performance pitfalls experienced when using the Qt framework. In the following chapters, you’ll explore multithreading and asynchronous programming with C++ and Qt and learn the importance and efficient use of data structures. You'll also get the opportunity to work through techniques such as memory management and design guidelines, which are essential to improve application performance. Comprehensive sections that cover all these concepts will prepare you for gaining hands-on experience of some of Qt's most exciting application fields - the mobile and embedded development domains. By the end of this book, you'll be ready to build Qt applications that are more efficient, concurrent, and performance-oriented in nature What you will learn * Understand classic performance best practices * Get to grips with modern hardware architecture and its performance impact * Implement tools and procedures used in performance optimization * Grasp Qt-specific work techniques for graphical user interface (GUI) and platform programming * Make Transmission Control Protocol (TCP) and Hypertext Transfer Protocol (HTTP) performant and use the relevant Qt classes * Discover the improvements Qt 5.9 (and the upcoming versions) holds in store * Explore Qt's graphic engine architecture, strengths, and weaknesses Who this book is for This book is designed for Qt developers who wish to build highly performance applications for desktop and embedded devices. Programming Experience with C++ is required.

Mivel az informatika egyre inkább átsz?vi életünket, a szoftverek min?ségével kapcsolatos elvárások egyre magasabbak. Egy szoftver el?állítása azonban nem csak programozásból áll, és a programozóktól sem lehet elvárni emberfeletti képességeket, a megrendel? el nem mondott elképzelésének t?kéletesen megfelel?, teljesen hibamentes munkát, mivel csak az nem hibázik, aki nem is dolgozik. Az informatika világában a szoftvertesztel?k azok, akik a szoftverek min?ségéért dolgoznak. A szoftvertesztel?k?n óriási felel?sség nyugszik és folyamatosan elvárások kereszttüzében kell helytállniuk. Mégis, szoftvertesztelés nélkül a legt?bb szoftver el sem jutna a felhasználókig, vagy ha igen, akkor megjelenésük botrányokkal, valamint óriási anyagi és erk?lcsi veszteségekkel járna együtt, a rengeteg fel nem tárt programhiba miatt. Szoftvertesztelésre és tesztel?kre ezért mindenképp szükség van. K?nyvünk a professzionális szoftvertesztelés alapjaival ismerteti meg az olvasót, számos gyakorlati példával f?szerezve, mell?zve a száraz, pusztán technikai megk?zelítés? leírásokat, kezdve a szoftvertesztelés általános bemutatásától, a fogalmak ismertetését?l, majd részleteiben tárgyalva a szoftvertesztelést és annak helyét a fejlesztési folyamatokban. Segítségével jó adag gyakorlati ismerettel vértezhetjük fel magunkat, melynek során valódi, a tesztelést támogató alkalmazásokat ismerhetünk meg, biztos alapot nyújtva a szoftvertesztelésben elhelyezked? leend? és gyakorló szakembereknek a mindennapi munkájukhoz. A szoftverteszteléssel most ismerked? szakembereknek és laikusoknak kimondottan hasznos lehet ez a k?nyv, de fejleszt?k és cégvezet?k számára is tartogat hasznos információkat, melyek segítségével bevezethetik, illetve hatékonyabbá tehetik a szoftvertesztelést munkájuk során.

This book is intended for Python programmers interested in learning how to do natural language processing. Maybe you’ve learned the limits of regular expressions the hard way, or you’ve realized that human language cannot be deterministically parsed like a computer language. Perhaps you have more text than you know what to do with, and need automated ways to analyze and structure that text. This Cookbook will show you how to train and use statistical language models to process text in ways that are practically impossible with standard programming tools. A basic knowledge of Python and the basic text processing concepts is expected. Some experience with regular expressions will also be helpful.

Build mesmerizing visualizations, analytics, and logs from your data using Elasticsearch, Logstash, and Kibana About This Book Solve all your data analytics problems with the ELK stack Explore the power of Kibana4 search and visualizations built over Elasticsearch queries and learn about the features and plugins of Logstash Develop a complete data pipeline using the ELK stack Who This Book Is For If you are a developer or DevOps engineer interested in building a system that provides amazing insights and business metrics out of data sources, of various formats and types, using the open source technology stack that ELK provides, then this book is for you. Basic knowledge of Unix or any programming language will be helpful to make the most out of this book. What You Will Learn Install, configure, and run Elasticsearch, Logstash, and Kibana Understand the need for log analytics and the current challenges in log analysis Build your own data pipeline using the ELK stack Familiarize yourself with the key features of Logstash and the variety of input, filter, and output plugins it provides Build your own custom Logstash plugin Create actionable insights using charts, histograms, and quick search features in Kibana4 Understand the role of Elasticsearch in the ELK stack In Detail The ELK stack—Elasticsearch, Logstash, and Kibana, is a powerful combination of open source tools. Elasticsearch is for deep search and data analytics. Logstash is for centralized logging, log enrichment, and parsing. Kibana is for powerful and beautiful data visualizations. In short, the Elasticsearch ELK stack makes searching and analyzing data easier than ever before. This book will introduce you to the ELK (Elasticsearch, Logstash, and Kibana) stack, starting by showing you how to set up the stack by installing the tools, and basic configuration. You’ll move on to building a basic data pipeline using the ELK stack. Next, you’ll explore the key features of Logstash and its role in the ELK stack, including creating Logstash plugins, which will enable you to use your own customized plugins. The importance of Elasticsearch and Kibana in the ELK stack is also covered, along with various types of advanced data analysis, and a variety of charts, tables ,and maps. Finally, by the end of the book you will be able to develop full-fledged data pipeline using the ELK stack and have a solid understanding of the role of each of the components. Style and approach This book is a step-by-step guide, complete with various examples to solve your data analytics problems by using the ELK stack to explore and visualize data.

The examples in this book follow a sample project creating a digital newspaper website to meet the requirements of a fictional customer who wants to place commercial advertisements all over the site. The whole book is a comprehensive collection of recipes that elaborate a series of well known use cases. You will find an organized step-by-step procedure to accomplish each task followed by detailed explanations to better understand how and why each topic was undertaken, and many links to online references and other related sections in the book that can supplement the subject in question. You can read the whole book or just pick the recipes that are relevant for you; where necessary, cross references will help you understand the recipes even if you do not read them in sequential order. This book is for programmers who have some knowledge of Python, Plone, and Zope. If you want to develop feature-rich add-on products in Plone, this book is for you. It is aimed at the development of backend features, so you need not have other web-related skills such as HTML, CSS, or JavaScript.

This book follows a standard tutorial approach with approximately 750 code samples spread through the 19 chapters. This amounts to over 5,900 lines of code that illustrate each concept. This book is aimed at programmers who have already learned the basics of objectoriented Python and need to write more sophisticated, flexible code that integrates seamlessly with the rest of Python. This book assumes a computer science background, with experience of common Python design patterns.

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book Leverage Python’s most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets Who This Book Is For If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn Explore how to use different machine learning models to ask different questions of your data Learn how to build neural networks using Keras and Theano Find out how to write clean and elegant Python code that will optimize the strength of your algorithms Discover how to embed your machine learning model in a web application for increased accessibility Predict continuous target outcomes using regression analysis Uncover hidden patterns and structures in data with clustering Organize data using effective pre-processing techniques Get to grips with sentiment analysis to delve deeper into textual and social media data In Detail Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world’s leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you’ll soon be able to answer some of the most important questions facing you and your organization. Style and approach Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.

Written as an interactive tutorial, this book covers the core of Kali Linux with realworld examples and stepbystep instructions to provide professional guidelines and recommendations for you. The book is designed in a simple and intuitive manner that allows you to explore the whole Kali Linux testing process or study parts of it individually. If you are an IT security professional who has a basic knowledge of Unix/Linux operating systems, including an awareness of information security factors, and want to use Kali Linux for penetration testing, then this book is for you.

A handson guide with projects based on fictitious, but common, application development briefs, which will illustrate practical ways of applying responsive web design with Bootstrap. Whether you are a beginner or intermediate web developer, if you wish to make the most of Bootstrap, then this book is for you. You should be familiar with the fundamentals of HTML and CSS, and have some experience incorporating JavaScript plugins. Prior Bootstrap experience is optional.

"Learning PowerCLI" is written in a friendly and practical style with a focus on getting you started and automating daily tasks quickly and efficiently. If you manage or administrate a vSphere environment, and want to make that easier and more efficient, then this book is for you! This book is ideal for you if you want to learn how to automate your VMware vSphere infrastructure, by getting the most out of PowerCLI. It’s assumed that you have some experience in administrating a VMware vSphere environment. Knowledge of Microsoft’s Windows PowerShell is not a prerequisite.

If you are an experienced Java developer using Java 7 platform and want to get your grips on OpenJDK for Java development, this is the book for you. JDK users who wish to migrate to OpenJDK will find this book very useful.