Recipes to help you build computer vision applications that make the most of the popular C++ library OpenCV 3 About This Book Written to the latest, gold-standard specification of OpenCV 3 Master OpenCV, the open source library of the computer vision community Master fundamental concepts in computer vision and image processing Learn about the important classes and functions of OpenCV with complete working examples applied to real images Who This Book Is For OpenCV 3 Computer Vision Application Programming Cookbook Third Edition is appropriate for novice C++ programmers who want to learn how to use the OpenCV library to build computer vision applications. It is also suitable for professional software developers who wish to be introduced to the concepts of computer vision programming. It can also be used as a companion book for university-level computer vision courses. It constitutes an excellent reference for graduate students and researchers in image processing and computer vision. What You Will Learn Install and create a program using the OpenCV library Process an image by manipulating its pixels Analyze an image using histograms Segment images into homogenous regions and extract meaningful objects Apply image filters to enhance image content Exploit the image geometry in order to relay different views of a pictured scene Calibrate the camera from different image observations Detect people and objects in images using machine learning techniques Reconstruct a 3D scene from images In Detail Making your applications see has never been easier with OpenCV. With it, you can teach your robot how to follow your cat, write a program to correctly identify the members of One Direction, or even help you find the right colors for your redecoration. OpenCV 3 Computer Vision Application Programming Cookbook Third Edition provides a complete introduction to the OpenCV library and explains how to build your first computer vision program. You will be presented with a variety of computer vision algorithms and exposed to important concepts in image and video analysis that will enable you to build your own computer vision applications. This book helps you to get started with the library, and shows you how to install and deploy the OpenCV library to write effective computer vision applications following good programming practices. You will learn how to read and write images and manipulate their pixels. Different techniques for image enhancement and shape analysis will be presented. You will learn how to detect specific image features such as lines, circles or corners. You will be introduced to the concepts of mathematical morphology and image filtering. The most recent methods for image matching and object recognition are described, and you’ll discover how to process video from files or cameras, as well as how to detect and track moving objects. Techniques to achieve camera calibration and perform multiple-view analysis will also be explained. Finally, you’ll also get acquainted with recent approaches in machine learning and object classification. Style and approach This book will arm you with the basics you need to start writing world-aware applications right from a pixel level all the way through to processing video sequences.

Utilize the power of modular programming to improve code readability, maintainability, and testability About This Book This book demonstrates code reusability and distributed development to get high speed, maintainable, and fast applications It illustrates the development of a complete modular application developed using PHP7 in detail This book provides a high-level overview of the Symfony framework, a set of tools and a development methodology that are needed to build a modular web shop application Who This Book Is For This step-by-step guide is divided into two sections. The first section explores all the fundamentals of modular design technique with respect to PHP 7. The latter section demonstrates the practical development of individual modules of a web shop application. What You Will Learn Discover the new features of PHP 7 that are relevant to modular application development Write manageable code based on the GoF design patterns and SOLID principles Define the application requirements of a working modular application Explore the ins and outs of the Symfony framework Build a set of modules based on the Symfony framework that comprise a simple web shop app Use core modules to set the structure and dependencies for other modules to use Set up entities that are relevant to the module functionality and see how to manage these entities In Detail Modular design techniques help you build readable, manageable, reusable, and more efficient codes. PHP 7, which is a popular open source *ing language, is used to build modular functions for your software. With this book, you will gain a deep insight into the modular programming paradigm and how to achieve modularity in your PHP code. We start with a brief introduction to the new features of PHP 7, some of which open a door to new concepts used in modular development. With design patterns being at the heart of all modular PHP code, you will learn about the GoF design patterns and how to apply them. You will see how to write code that is easy to maintain and extend over time with the help of the SOLID design principles. Throughout the rest of the book, you will build different working modules of a modern web shop application using the Symfony framework, which will give you a deep understanding of modular application development using PHP 7. Style and approach This book is for intermediate-level PHP developers with little to no knowledge of modular programming who want to understand design patterns and principles in order to better utilize the existing frameworks for modular application development.

Develop real-world applications in Windows. About This Book Create diverse applications featuring the versatility of Small Windows C++ library Learn about object-oriented programming in Windows and how to develop a large object-oriented class library in C++ Understand how to tackle application-specific problems along with acquiring a deep understanding of the workings of Windows architecture Who This Book Is For This book is for application developers who want a head-first approach into Windows programming. It will teach you how to develop an object-oriented class library in C++ and enhanced applications in Windows. Basic knowledge of C++ and the object-oriented framework is assumed to get the most out of this book. What You Will Learn Develop advanced real-world applications in Windows Design and implement a graphical object-oriented class library in C++ Get to grips with the workings of the integral aspects of the Win32 API, such as mouse input, drawing, cut-and-paste, file handling, and drop files Identify general problems when developing graphical applications as well as specific problems regarding drawing, spreadsheet, and word processing applications Implement classes, functions, and macros of the object-oriented class library developed in the book and how we implement its functionality by calling functions and macros in the Win32 API In Detail It is critical that modern developers have the right tools to build practical, user-friendly, and efficient applications in order to compete in today’s market. Through hands-on guidance, this book illustrates and demonstrates C++ best practices and the Small Windows object-oriented class library to ease your development of interactive Windows applications. Begin with a focus on high level application development using Small Windows. Learn how to build four real-world applications which focus on the general problems faced when developing graphical applications. Get essential troubleshooting guidance on drawing, spreadsheet, and word processing applications. Finally finish up with a deep dive into the workings of the Small Windows class library, which will give you all the insights you need to build your own object-oriented class library in C++. Style and approach This book takes a tutorial-style approach that will demonstrate the features of a C++ object-oriented library by developing interactive Windows applications.

Boost the performance of your Haskell applications using optimization, concurrency, and parallel programming About This Book Explore the benefits of lazy evaluation, compiler features, and tools and libraries designed for high performance Write fast programs at extremely high levels of abstraction Work through practical examples that will help you address the challenges of writing efficient code Who This Book Is For To get the most out of this book, you need to have a working knowledge of reading and writing basic Haskell. No knowledge of performance, optimization, or concurrency is required. What You Will Learn Program idiomatic Haskell that's also surprisingly efficient Improve performance of your code with data parallelism, inlining, and strictness annotations Profile your programs to identify space leaks and missed opportunities for optimization Find out how to choose the most efficient data and control structures Optimize the Glasgow Haskell Compiler and runtime system for specific programs See how to smoothly drop to lower abstractions wherever necessary Execute programming for the GPU with Accelerate Implement programming to easily scale to the cloud with Cloud Haskell In Detail Haskell, with its power to optimize the code and its high performance, is a natural candidate for high performance programming. It is especially well suited to stacking abstractions high with a relatively low performance cost. This book addresses the challenges of writing efficient code with lazy evaluation and techniques often used to optimize the performance of Haskell programs. We open with an in-depth look at the evaluation of Haskell expressions and discuss optimization and benchmarking. You will learn to use parallelism and we'll explore the concept of streaming. We’ll demonstrate the benefits of running multithreaded and concurrent applications. Next we’ll guide you through various profiling tools that will help you identify performance issues in your program. We’ll end our journey by looking at GPGPU, Cloud and Functional Reactive Programming in Haskell. At the very end there is a catalogue of robust library recommendations with code samples. By the end of the book, you will be able to boost the performance of any app and prepare it to stand up to real-world punishment. Style and approach This easy-to-follow guide teaches new practices and techniques to optimize your code, and then moves towards more advanced ways to effectively write efficient Haskell code. Small and simple practical examples will help you test the concepts yourself, and you will be able to easily adapt them for any application.

Explore the world of data science from scratch with Julia by your side About This Book An in-depth exploration of Julia's growing ecosystem of packages Work with the most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn about deep learning using Mocha.jl and give speed and high performance to data analysis on large data sets Who This Book Is For This book is aimed at data analysts and aspiring data scientists who have a basic knowledge of Julia or are completely new to it. The book also appeals to those competent in R and Python and wish to adopt Julia to improve their skills set in Data Science. It would be beneficial if the readers have a good background in statistics and computational mathematics. What You Will Learn Apply statistical models in Julia for data-driven decisions Understanding the process of data munging and data preparation using Julia Explore techniques to visualize data using Julia and D3 based packages Using Julia to create self-learning systems using cutting edge machine learning algorithms Create supervised and unsupervised machine learning systems using Julia. Also, explore ensemble models Build a recommendation engine in Julia Dive into Julia’s deep learning framework and build a system using Mocha.jl In Detail Julia is a fast and high performing language that's perfectly suited to data science with a mature package ecosystem and is now feature complete. It is a good tool for a data science practitioner. There was a famous post at Harvard Business Review that Data Scientist is the sexiest job of the 21st century. (https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the-21st-century). This book will help you get familiarised with Julia's rich ecosystem, which is continuously evolving, allowing you to stay on top of your game. This book contains the essentials of data science and gives a high-level overview of advanced statistics and techniques. You will dive in and will work on generating insights by performing inferential statistics, and will reveal hidden patterns and trends using data mining. This has the practical coverage of statistics and machine learning. You will develop knowledge to build statistical models and machine learning systems in Julia with attractive visualizations. You will then delve into the world of Deep learning in Julia and will understand the framework, Mocha.jl with which you can create artificial neural networks and implement deep learning. This book addresses the challenges of real-world data science problems, including data cleaning, data preparation, inferential statistics, statistical modeling, building high-performance machine learning systems and creating effective visualizations using Julia. Style and approach This practical and easy-to-follow yet comprehensive guide will get you learning about Julia with respect to data science. Each topic is explained thoroughly and placed in context. For the more inquisitive, we dive deeper into the language and its use case. This is the one true guide to working with Julia in data science.

A practical guide to obtaining, transforming, exploring, and analyzing data using Python, MongoDB, and Apache Spark About This Book Learn to use various data analysis tools and algorithms to classify, cluster, visualize, simulate, and forecast your data Apply Machine Learning algorithms to different kinds of data such as social networks, time series, and images A hands-on guide to understanding the nature of data and how to turn it into insight Who This Book Is For This book is for developers who want to implement data analysis and data-driven algorithms in a practical way. It is also suitable for those without a background in data analysis or data processing. Basic knowledge of Python programming, statistics, and linear algebra is assumed. What You Will Learn Acquire, format, and visualize your data Build an image-similarity search engine Generate meaningful visualizations anyone can understand Get started with analyzing social network graphs Find out how to implement sentiment text analysis Install data analysis tools such as Pandas, MongoDB, and Apache Spark Get to grips with Apache Spark Implement machine learning algorithms such as classification or forecasting In Detail Beyond buzzwords like Big Data or Data Science, there are a great opportunities to innovate in many businesses using data analysis to get data-driven products. Data analysis involves asking many questions about data in order to discover insights and generate value for a product or a service. This book explains the basic data algorithms without the theoretical jargon, and you’ll get hands-on turning data into insights using machine learning techniques. We will perform data-driven innovation processing for several types of data such as text, Images, social network graphs, documents, and time series, showing you how to implement large data processing with MongoDB and Apache Spark. Style and approach This is a hands-on guide to data analysis and data processing. The concrete examples are explained with simple code and accessible data.

Analyze your data and delve deep into the world of machine learning with the latest Spark version, 2.0 About This Book Perform data analysis and build predictive models on huge datasets that leverage Apache Spark Learn to integrate data science algorithms and techniques with the fast and scalable computing features of Spark to address big data challenges Work through practical examples on real-world problems with sample code snippets Who This Book Is For This book is for anyone who wants to leverage Apache Spark for data science and machine learning. If you are a technologist who wants to expand your knowledge to perform data science operations in Spark, or a data scientist who wants to understand how algorithms are implemented in Spark, or a newbie with minimal development experience who wants to learn about Big Data Analytics, this book is for you! What You Will Learn Consolidate, clean, and transform your data acquired from various data sources Perform statistical analysis of data to find hidden insights Explore graphical techniques to see what your data looks like Use machine learning techniques to build predictive models Build scalable data products and solutions Start programming using the RDD, DataFrame and Dataset APIs Become an expert by improving your data analytical skills In Detail This is the era of Big Data. The words ‘Big Data’ implies big innovation and enables a competitive advantage for businesses. Apache Spark was designed to perform Big Data analytics at scale, and so Spark is equipped with the necessary algorithms and supports multiple programming languages. Whether you are a technologist, a data scientist, or a beginner to Big Data analytics, this book will provide you with all the skills necessary to perform statistical data analysis, data visualization, predictive modeling, and build scalable data products or solutions using Python, Scala, and R. With ample case studies and real-world examples, Spark for Data Science will help you ensure the successful execution of your data science projects. Style and approach This book takes a step-by-step approach to statistical analysis and machine learning, and is explained in a conversational and easy-to-follow style. Each topic is explained sequentially with a focus on the fundamentals as well as the advanced concepts of algorithms and techniques. Real-world examples with sample code snippets are also included.

The latest in modern Python recipes for the busy modern programmer About This Book Develop succinct, expressive programs in Python Learn the best practices and common idioms through carefully explained and structured recipes Discover new ways to apply Python for the new age of development Who This Book Is For The book is for web developers, programmers, enterprise programmers, engineers, big data scientist, and so on. If you are a beginner, Python Cookbook will get you started. If you are experienced, it will expand your knowledge base. A basic knowledge of programming would help. What You Will Learn See the intricate details of the Python syntax and how to use it to your advantage Improve your code readability through functions in Python Manipulate data effectively using built-in data structures Get acquainted with advanced programming techniques in Python Equip yourself with functional and statistical programming features Write proper tests to be sure a program works as advertised Integrate application software using Python In Detail Python is the preferred choice of developers, engineers, data scientists, and hobbyists everywhere. It is a great *ing language that can power your applications and provide great speed, safety, and scalability. By exposing Python as a series of simple recipes, you can gain insight into specific language features in a particular context. Having a tangible context helps make the language or standard library feature easier to understand. This book comes with over 100 recipes on the latest version of Python. The recipes will benefit everyone ranging from beginner to an expert. The book is broken down into 13 chapters that build from simple language concepts to more complex applications of the language. The recipes will touch upon all the necessary Python concepts related to data structures, OOP, functional programming, as well as statistical programming. You will get acquainted with the nuances of Python syntax and how to effectively use the advantages that it offers. You will end the book equipped with the knowledge of testing, web services, and configuration and application integration tips and tricks. The recipes take a problem-solution approach to resolve issues commonly faced by Python programmers across the globe. You will be armed with the knowledge of creating applications with flexible logging, powerful configuration, and command-line options, automated unit tests, and good documentation. Style and approach This book takes a recipe-based approach, where each recipe addresses specific problems and issues. The recipes provide discussions and insights and an explanation of the problems.

"Key Features ?Identify design issues and make the necessary adjustments to achieve improved performance ?Understand practical architectural quality attributes from the perspective of a practicing engineer and architect using Python ?Gain knowledge of architectural principles and how they can be used to provide accountability and rationale for architectural decisions Book De*ion This book starts off by explaining how Python fits into an application architecture. As you move along, you will understand the architecturally significant demands and how to determine them. Later, you'll get a complete understanding of the different architectural quality requirements that help an architect to build a product that satisfies business needs, such as maintainability/reusability, testability, scalability, performance, usability, and security. You will use various techniques such as incorporating DevOps, Continuous Integration, and more to make your application robust. You will understand when and when not to use object orientation in your applications. You will be able to think of the future and design applications that can scale proportionally to the growing business. The focus is on building the business logic based on the business process documentation and which frameworks are to be used when. We also cover some important patterns that are to be taken into account while solving design problems as well as those in relatively new domains such as the Cloud. This book will help you understand the ins and outs of Python so that you can make those critical design decisions that not just live up to but also surpass the expectations of your clients. What you will learn ?Build programs with the right architectural attributes ?Use Enterprise Architectural Patterns to solve scalable problems on the Web ?Understand design patterns from a Python perspective ?Optimize the performance testing tools in Python ?Deploy code in remote environments or on the Cloud using Python ?Secure architecture applications in Python About the Author Anand Balachandran Pillai is an Engineering and Technology professional with over 18 years of experience in the software industry in Product Engineering, Software Design & Architecture and Research. He has a Bachelor's degree in Mechanical Engineering from the Indian Institute of Technology, Madras. He has worked at companies such as Yahoo!, McAfee, and Infosys in the roles of Lead Engineer and Architect in product development teams, to build new products. His interests lie in Software Performance Engineering, High Scalability Architectures, Security and Open source communities. He often works with startups in lead technical or consulting role. He is the founder of the Bangalore Python Users Group and a Fellow of the Python Software Foundation (PSF). Anand is currently working as Senior Architect of Yegii Inc. "

This book will teach you advanced techniques in machine learning with the latest code in R 3.3.2. You will delve into statistical learning theory and supervised learning; design efficient algorithms; learn about creating Recommendation Engines; use multi-class classification and deep learning; and more. You will explore, in depth, topics such as data mining, classification, clustering, regression, predictive modeling, anomaly detection, boosted trees with XGBOOST, and more. More than just knowing the outcome, you'll understand how these concepts work and what they do. With a slow learning curve on topics such as neural networks, you will explore deep learning, and more. By the end of this book, you will be able to perform machine learning with R in the cloud using AWS in various scenarios with different datasets. What you will learn ?Gain deep insights into the application of machine learning tools in the industry ?Manipulate data in R efficiently to prepare it for analysis ?Master the skill of recognizing techniques for effective visualization of data ?Understand why and how to create test and training data sets for analysis ?Master fundamental learning methods such as linear and logistic regression ?Comprehend advanced learning methods such as support vector

"Kali Linux Network Scanning Cookbook" is intended for information security professionals and casual security enthusiasts alike. It will provide the foundational principles for the novice reader but will also introduce *ing techniques and in-depth analysis for the more advanced audience. Whether you are brand new to Kali Linux or a seasoned veteran, this book will aid in both understanding and ultimately mastering many of the most powerful and useful scanning techniques in the industry. It is assumed that the reader has some basic security testing experience.

From a cutting-edge cultural commentator, a bold and brilliant challenge to cherished notions of the internet as the great leveler of our age. The internet has been hailed as an unprecedented democratising force, a place where everyone can participate. ? So why are minorities and marginalized groups under-represented on user-generated websites, with less than 15% of Wikipedia written by women? ? Why does keyword-jammed and star-studded churnalism proliferate, at the expense of in-depth, investigative journalism? ? And how have a handful of giant corporations like Facebook, Google and Apple seized control of our creativity, galvanizing individuals to produce content for free? ‘The People’s Platform’ argues that for all our ‘sharing’, the internet reflects real-world inequalities as much as it reduces them, as attention and income frequently accrue to those who already have plenty of both. The online world does offer a unique opportunity for greater freedom, but a community that supports the diverse and lasting will not spring up from technology alone. If we want the internet to be a people’s platform, we will have to make it so.

This book is for 3D Artists and Designers who want to learn efficient building of 3D Animations. Knowledge of 3D Modeling is essential but no prior experience with Blender is required.

If you are a system administrator who has some experience with virtualization and already uses VMware vCenter, but wishes to learn more, then this is the book for you. If you are looking for tips or shortcuts for common administration tasks as well as workarounds for pain points in vSphere administration, you'll find this guide useful.

If you have intermediate-level knowledge of Python and are well aware of the main research and vocabulary in your bioinformatics topic of interest, this book will help you develop your knowledge further.

If you are a Python developer who wants to master the world of data science, then this book is for you. Some knowledge of data science is assumed.

Written in a cookbook style, this book will teach you through the use of recipes with examples and illustrations. Each recipe contains step-by-step instructions about everything necessary to execute a particular task.This book is intended for both BI and database developers who want to expand their knowledge of MicroStrategy. It is also useful for advanced data analysts who are evaluating different technologies. You do not need to be an SQL master to read this book, yet knowledge of some concepts like foreign keys and many-to-many relationships is assumed. Some knowledge of basic concepts such as dimensional modeling (fact tables, dimensions) will also help your comprehension of this book. No previous MicroStrategy knowledge is needed.

This is a practical, tutorial-style book that includes many examples that demonstrate how to develop EJB 3.0 database persistence applications with Oracle Fusion Middleware 11g. Every chapter starts with setting the environment for the chapter and includes an example application illustrated with figures at milestone stages. This book is aimed at EJB 3.0 application developers who want to learn about the practical use of EJB 3.0 database persistence with Oracle Fusion Middleware. Those who are already using EJB 3.0 database persistence will learn about using EJB 3.0 database persistence with Oracle Fusion Middleware 11g. The target audience is expected to have some prior knowledge about Java EE, EJBs, EJB 3.0, JSF, AJAX, web services, and XML. This book is ideal for those developers who have working knowledge of JDeveloper and WebLogic server, and wish to learn about the practical use of EJB 3.0 with Oracle Fusion Middleware.

This practical cookbook covers a broad range of topics in an easytounderstand manner. Stepbystep instructions guide you through even the most complicated of tools in Minitab. This book is great for anyone who is familiar with statistics and who wants to learn how Minitab works. Whilst you do not need to be an expert in all areas of statistics, you should understand the basics of the chapters you are interested in.

A practical guide packed with stepbystep recipes to design a virtual datacenter using VMware 5.x This book is a guide for anyone interested in designing virtualized datacenters using VMware vSphere 5.x and the supporting components. Current administrators of VMware vSphere environments will find this book useful when interested in becoming a vSphere Architect or are interested in learning more about the virtual datacenter design process. Knowledge of vSphere installation, configuration, and administration is a prerequisite.

A comprehensive guide to mastering the most advanced Hadoop 3 concepts Key Features * Get to grips with the newly introduced features and capabilities of Hadoop 3 * Crunch and process data using MapReduce, YARN, and a host of tools within the Hadoop ecosystem * Sharpen your Hadoop skills with real-world case studies and code Book Description Apache Hadoop is one of the most popular big data solutions for distributed storage and for processing large chunks of data. With Hadoop 3, Apache promises to provide a high-performance, more fault-tolerant, and highly efficient big data processing platform, with a focus on improved scalability and increased efficiency. With this guide, you’ll understand advanced concepts of the Hadoop ecosystem tool. You’ll learn how Hadoop works internally, study advanced concepts of different ecosystem tools, discover solutions to real-world use cases, and understand how to secure your cluster. It will then walk you through HDFS, YARN, MapReduce, and Hadoop 3 concepts. You’ll be able to address common challenges like using Kafka efficiently, designing low latency, reliable message delivery Kafka systems, and handling high data volumes. As you advance, you’ll discover how to address major challenges when building an enterprise-grade messaging system, and how to use different stream processing systems along with Kafka to fulfil your enterprise goals. By the end of this book, you’ll have a complete understanding of how components in the Hadoop ecosystem are effectively integrated to implement a fast and reliable data pipeline, and you’ll be equipped to tackle a range of real-world problems in data pipelines. What you will learn * Gain an in-depth understanding of distributed computing using Hadoop 3 * Develop enterprise-grade applications using Apache Spark, Flink, and more * Build scalable and high-performance Hadoop data pipelines with security, monitoring, and data governance * Explore batch data processing patterns and how to model data in Hadoop * Master best practices for enterprises using, or planning to use, Hadoop 3 as a data platform * Understand security aspects of Hadoop, including authorization and authentication Who this book is for If you want to become a big data professional by mastering the advanced concepts of Hadoop, this book is for you. You’ll also find this book useful if you’re a Hadoop professional looking to strengthen your knowledge of the Hadoop ecosystem. Fundamental knowledge of the Java programming language and basics of Hadoop is necessary to get started with this book.