The book requires no prior knowledge of JavaScript and works from the ground up to give you a thorough grounding in this powerful language. If you do already know some JavaScript, you will find plenty of eye-openers as you discover just what the language can do. This book takes a do-it-yourself approach when it comes to writing code, because the best way to really learn a programming language is by writing code. You are encouraged to type code into Firebug's console, see how it works and then tweak it and play around with it. There are practice questions at the end of each chapter to help review what you have learned.

This book takes a practical approach, implementing all theoretical concepts with examples. It is a fast-paced tutorial that focuses on critical decisions that you need to make every time you build MySQL databases. It is rich with tips and advice from an experienced practitioner. Anyone working with applications that use a MySQL database backend will benefit greatly from the advice and techniques in this book. Although a working knowledge of both SQL and MySQL is assumed, the book is suitable for both beginners and intermediate users alike. Whether you read it through and absorb the advice or work through it on a live project, the efficiency and maintainability of your databases will certainly improve as a result.

Written in cookbook style, this book offers many recipes to create objects, import and export data, create 3D solid objects. Each recipe contains step-by-step instructions followed by analysis of what was done in each task and other useful information. If you've been toying around with FreeCAD and want to have more control over your work flow then this book is for you. The reader needs to have basic knowledge of modeling.

Be an adaptive thinker that leads the way to Artificial Intelligence About This Book ? AI-based examples to guide you in designing and implementing machine intelligence ? Develop your own method for future AI solutions ? Acquire advanced AI, machine learning, and deep learning design skills Who This Book Is For Artificial Intelligence by Example is a simple, explanatory, and descriptive guide for junior developers, experienced developers, technology consultants, and those interested in AI who want to understand the fundamentals of Artificial Intelligence and implement it practically by devising smart solutions. Prior experience with Python and statistical knowledge is essential to make the most out of this book. What You Will Learn ? Use adaptive thinking to solve real-life AI case studies ? Rise beyond being a modern-day factory code worker ? Acquire advanced AI, machine learning, and deep learning designing skills ? Learn about cognitive NLP chatbots, quantum computing, and IoT and blockchain technology ? Understand future AI solutions and adapt quickly to them ? Develop out-of-the-box thinking to face any challenge the market presents In Detail Artificial Intelligence has the potential to replicate humans in every field. This book serves as a starting point for you to understand how AI is built, with the help of intriguing examples and case studies. Artificial Intelligence By Example will make you an adaptive thinker and help you apply concepts to real-life scenarios. Using some of the most interesting AI examples, right from a simple chess engine to a cognitive chatbot, you will learn how to tackle the machine you are competing with. You will study some of the most advanced machine learning models, understand how to apply AI to blockchain and IoT, and develop emotional quotient in chatbots using neural networks. You will move on to designing AI solutions in a simple manner rather than get confused by complex architectures and techniques. This comprehensive guide will be a starter kit for you to develop AI applications on your own. By the end of this book, will have understood the fundamentals of AI and worked through a number of case studies that will help you develop business vision. Style and approach An easy-to-follow step by step guide which will help you get to grips with real world application of Artificial Intelligence

"Take your machine learning skills to the next level by mastering Deep Learning concepts and algorithms using Python. About This Book ?Explore and create intelligent systems using cutting-edge deep learning techniques ?Implement deep learning algorithms and work with revolutionary libraries in Python ?Get real-world examples and easy-to-follow tutorials on Theano, TensorFlow, H2O and more Who This Book Is For This book is for Data Science practitioners as well as aspirants who have a basic foundational understanding of Machine Learning concepts and some programming experience with Python. A mathematical background with a conceptual understanding of calculus and statistics is also desired. What You Will Learn ?Get a practical deep dive into deep learning algorithms ?Explore deep learning further with Theano, Caffe, Keras, and TensorFlow ?Learn about two of the most powerful techniques at the core of many practical deep learning implementations: Auto-Encoders and Restricted Boltzmann Machines ?Dive into Deep Belief Nets and Deep Neural Networks ?Discover more deep learning algorithms with Dropout and Convolutional Neural Networks ?Get to know device strategies so you can use deep learning algorithms and libraries in the real world In Detail With an increasing interest in AI around the world, deep learning has attracted a great deal of public attention. Every day, deep learning algorithms are used broadly across different industries. The book will give you all the practical information available on the subject, including the best practices, using real-world use cases. You will learn to recognize and extract information to increase predictive accuracy and optimize results. Starting with a quick recap of important machine learning concepts, the book will delve straight into deep learning principles using Sci-kit learn. Moving ahead, you will learn to use the latest open source libraries such as Theano, Keras, Google's TensorFlow, and H20. Use this guide to uncover the difficulties of pattern recognition, scaling data with greater accuracy and discussing deep learning algorithms and techniques. Whether you want to dive deeper into Deep Learning, or want to investigate how to get more out of this powerful technology, you'll find everything inside. Style and approach Python Machine Learning by example follows practical hands on approach. It walks you through the key elements of Python and its powerful machine learning libraries with the help of real world projects. "

If you are a Python beginner who is looking to learn the language through interesting projects, this book is for you. A basic knowledge of programming and statistics is beneficial to get the most out of the book.

A step-by-step guide, packed with examples of practical numerical analysis that will give you a comprehensive, but concise overview of NumPy. This book is for programmers, scientists, or engineers, who have basic Python knowledge and would like to be able to do numerical computations with Python.

If you are a professional or enthusiast who has a basic understanding of graphs or has basic knowledge of Neo4j operations, this is the book for you. Although it is targeted at an advanced user base, this book can be used by beginners as it touches upon the basics. So, if you are passionate about taming complex data with the help of graphs and building high performance applications, you will be able to get valuable insights from this book.

Use Python and NLTK (Natural Language Toolkit) to build out your own text classifiers and solve common NLP problems. Key Features * Assimilate key NLP concepts and terminologies * Explore popular NLP tools and techniques * Gain practical experience using NLP in application code Book Description If NLP hasn't been your forte, Natural Language Processing Fundamentals will make sure you set off to a steady start. This comprehensive guide will show you how to effectively use Python libraries and NLP concepts to solve various problems. You'll be introduced to natural language processing and its applications through examples and exercises. This will be followed by an introduction to the initial stages of solving a problem, which includes problem definition, getting text data, and preparing it for modeling. With exposure to concepts like advanced natural language processing algorithms and visualization techniques, you'll learn how to create applications that can extract information from unstructured data and present it as impactful visuals. Although you will continue to learn NLP-based techniques, the focus will gradually shift to developing useful applications. In these sections, you'll understand how to apply NLP techniques to answer questions as can be used in chatbots. By the end of this book, you'll be able to accomplish a varied range of assignments ranging from identifying the most suitable type of NLP task for solving a problem to using a tool like spacy or gensim for performing sentiment analysis. The book will easily equip you with the knowledge you need to build applications that interpret human language. What you will learn * Obtain, verify, and clean data before transforming it into a correct format for use * Perform data analysis and machine learning tasks using Python * Understand the basics of computational linguistics * Build models for general natural language processing tasks * Evaluate the performance of a model with the right metrics * Visualize, quantify, and perform exploratory analysis from any text data Who this book is for Natural Language Processing Fundamentals is designed for novice and mid-level data scientists and machine learning developers who want to gather and analyze text data to build an NLP-powered product. It'll help you to have prior experience of coding in Python using data types, writing functions, and importing libraries. Some experience with linguistics and probability is useful but not necessary.

Over 50 hands-on recipes that will help you develop amazing real-time applications using GPIO, RS232, ADC, DAC, timers, audio codecs, graphics LCD, and a touch screen About This Book This book focuses on programming embedded systems using a practical approach Examples show how to use bitmapped graphics and manipulate digital audio to produce amazing games and other multimedia applications The recipes in this book are written using ARM’s MDK Microcontroller Development Kit which is the most comprehensive and accessible development solution Who This Book Is For This book is aimed at those with an interest in designing and programming embedded systems. These could include electrical engineers or computer programmers who want to get started with microcontroller applications using the ARM Cortex-M4 architecture in a short time frame. The book’s recipes can also be used to support students learning embedded programming for the first time. Basic knowledge of programming using a high level language is essential but those familiar with other high level languages such as Python or Java should not have too much difficulty picking up the basics of embedded C programming. What You Will Learn Use ARM’s uVision MDK to configure the microcontroller run time environment (RTE), create projects and compile download and run simple programs on an evaluation board. Use and extend device family packs to configure I/O peripherals. Develop multimedia applications using the touchscreen and audio codec beep generator. Configure the codec to stream digital audio and design digital filters to create amazing audio effects. Write multi-threaded programs using ARM’s real time operating system (RTOS). Write critical sections of code in assembly language and integrate these with functions written in C. Fix problems using ARM’s debugging tool to set breakpoints and examine variables. Port uVision projects to other open source development environments. In Detail Embedded microcontrollers are at the core of many everyday electronic devices. Electronic automotive systems rely on these devices for engine management, anti-lock brakes, in car entertainment, automatic transmission, active suspension, satellite navigation, etc. The so-called internet of things drives the market for such technology, so much so that embedded cores now represent 90% of all processor’s sold. The ARM Cortex-M4 is one of the most powerful microcontrollers on the market and includes a floating point unit (FPU) which enables it to address applications. The ARM Cortex-M4 Microcontroller Cookbook provides a practical introduction to programming an embedded microcontroller architecture. This book attempts to address this through a series of recipes that develop embedded applications targeting the ARM-Cortex M4 device family. The recipes in this book have all been tested using the Keil MCBSTM32F400 board. This board includes a small graphic LCD touchscreen (320x240 pixels) that can be used to create a variety of 2D gaming applications. These motivate a younger audience and are used throughout the book to illustrate particular hardware peripherals and software concepts. C language is used predominantly throughout but one chapter is devoted to recipes involving assembly language. Programs are mostly written using ARM’s free microcontroller development kit (MDK) but for those looking for open source development environments the book also shows how to configure the ARM-GNU toolchain. Some of the recipes described in the book are the basis for laboratories and assignments undertaken by undergraduates. Style and approach The ARM Cortex-M4 Cookbook is a practical guide full of hands-on recipes. It follows a step-by-step approach that allows you to find, utilize and learn ARM concepts quickly.

A step-by-step, example-based guide to building immersive 3D games on the Web using the Three.js graphics library.This book is for people interested in programming 3D games for the Web. Readers are expected to have basic knowledge of JavaScript syntax and a basic understanding of HTML and CSS. This book will be useful regardless of prior experience with game programming, whether you intend to build casual side projects or large-scale professional titles.

Utilize proven solutions to solve common problems in game development About This Book ?Untangle your game development workflow, make cleaner code, and create structurally solid games ?Implement key programming patterns that will enable you to make efficient AI and remove duplication ?Optimize your game using memory management techniques Who This Book Is For If you are a game developer who wants to solve commonly-encountered issues or have some way to communicate to other developers in a standardized format, then this book is for you. Knowledge of basic game programming principles and C++ programming is assumed. What You Will Learn ?Learn what design patterns are and why you would want to use them ?Reduce the maintenance burden with well-tested, cleaner code ?Employ the singleton pattern effectively to reduce your compiler workload ?Use the factory pattern to help you create different objects with the same creation logic and reduce coding time ?Improve game performance with Object Pools ?Allow game play to interact with physics or graphics in an abstract way ?Refractor your code to remove common code smells In Detail You've learned how to program, and you've probably created some simple games at some point, but now you want to build larger projects and find out how to resolve your problems. So instead of a coder, you might now want to think like a game developer or software engineer. To organize your code well, you need certain tools to do so, and that's what this book is all about. You will learn techniques to

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

Demystify the complexity of machine learning techniques and create evolving, clever solutions to solve your problems Key Features *Master supervised, unsupervised, and semi-supervised ML algorithms and their implementation *Build deep learning models for object detection, image classification, similarity learning, and more *Build, deploy, and scale end-to-end deep neural network models in a production environment Book Description This Learning Path is your complete guide to quickly getting to grips with popular machine learning algorithms. You'll be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this Learning Path will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries. You'll bring the use of TensorFlow and Keras to build deep learning models, using concepts such as transfer learning, generative adversarial networks, and deep reinforcement learning. Next, you'll learn the advanced features of TensorFlow1.x, such as distributed TensorFlow with TF clusters, deploy production models with TensorFlow Serving. You'll implement different techniques related to object classification, object detection, image segmentation, and more. By the end of this Learning Path, you'll have obtained in-depth knowledge of TensorFlow, making you the go-to person for solving artificial intelligence problems This Learning Path includes content from the following Packt products: *Mastering Machine Learning Algorithms by Giuseppe Bonaccorso *Mastering TensorFlow 1.x by Armando Fandango *Deep Learning for Computer Vision by Rajalingappaa Shanmugamani What you will learn *Explore how an ML model can be trained, optimized, and evaluated *Work with Autoencoders and Generative Adversarial Networks *Explore the most important Reinforcement Learning techniques *Build end-to-end deep learning (CNN, RNN, and Autoencoders) models Who this book is for This Learning Path is for data scientists, machine learning engineers, artificial intelligence engineers who want to delve into complex machine learning algorithms, calibrate models, and improve the predictions of the trained model. You will encounter the advanced intricacies and complex use cases of deep learning and AI. A basic knowledge of programming in Python and some understanding of machine learning concepts are required to get the best out of this Learning Path.

Text processing and pattern matching simplified About This Book ? Master the fastest and most elegant big data munging language ? Implement text processing and pattern matching using the advanced features of AWK and GAWK ? Implement debugging and inter-process communication using GAWK Who This Book Is For This book is for developers or analysts who are inclined to learn how to do text processing and data extraction in a Unix-like environment. Basic understanding of Linux operating system and shell scripting will help you to get the most out of the book. What You Will Learn ? Create and use different expressions and control flow statements in AWK ? Use Regular Expressions with AWK for effective text-processing ? Use built-in and user-defined variables to write AWK programs ? Use redirections in AWK programs and create structured reports ? Handle non-decimal input, 2-way inter-process communication with Gawk ? Create small scripts to reformat data to match patterns and process texts In Detail AWK is one of the most primitive and powerful utilities which exists in all Unix and Unix-like distributions. It is used as a command-line utility when performing a basic text-processing operation, and as programming language when dealing with complex text-processing and mining tasks. With this book, you will have the required expertise to practice advanced AWK programming in real-life examples. The book starts off with an introduction to AWK essentials. You will then be introduced to regular expressions, AWK variables and constants, arrays and AWK functions and more. The book then delves deeper into more complex tasks, such as printing formatted output in AWK, control flow statements, GNU's implementation of AWK covering the advanced features of GNU AWK, such as network communication, debugging, and inter-process communication in the GAWK programming language which is not easily possible with AWK. By the end of this book, the reader will have worked on the practical implementation of text processing and pattern matching using AWK to perform routine tasks. Style and approach An easy-to-follow, step by step guide which will help you get to grips with real-world applications of AWK programming.

Get to grips with key data visualization and predictive analytic skills using R About This Book Acquire predictive analytic skills using various tools of R Make predictions about future events by discovering valuable information from data using R Comprehensible guidelines that focus on predictive model design with real-world data Who This Book Is For If you are a statistician, chief information officer, data scientist, ML engineer, ML practitioner, quantitative analyst, and student of machine learning, this is the book for you. You should have basic knowledge of the use of R. Readers without previous experience of programming in R will also be able to use the tools in the book. What You Will Learn Customize R by installing and loading new packages Explore the structure of data using clustering algorithms Turn unstructured text into ordered data, and acquire knowledge from the data Classify your observations using Na?ve Bayes, k-NN, and decision trees Reduce the dimensionality of your data using principal component analysis Discover association rules using Apriori Understand how statistical distributions can help retrieve information from data using correlations, linear regression, and multilevel regression Use PMML to deploy the models generated in R In Detail R is statistical software that is used for data analysis. There are two main types of learning from data: unsupervised learning, where the structure of data is extracted automatically; and supervised learning, where a labeled part of the data is used to learn the relationship or scores in a target attribute. As important information is often hidden in a lot of data, R helps to extract that information with its many standard and cutting-edge statistical functions. This book is packed with easy-to-follow guidelines that explain the workings of the many key data mining tools of R, which are used to discover knowledge from your data. You will learn how to perform key predictive analytics tasks using R, such as train and test predictive models for classification and regression tasks, score new data sets and so on. All chapters will guide you in acquiring the skills in a practical way. Most chapters also include a theoretical introduction that will sharpen your understanding of the subject matter and invite you to go further. The book familiarizes you with the most common data mining tools of R, such as k-means, hierarchical regression, linear regression, association rules, principal component analysis, multilevel modeling, k-NN, Na?ve Bayes, decision trees, and text mining. It also provides a de*ion of visualization techniques using the basic visualization tools of R as well as lattice for visualizing patterns in data organized in groups. This book is invaluable for anyone fascinated by the data mining opportunities offered by GNU R and its packages. Style and approach This is a practical book, which analyzes compelling data about life, health, and death with the help of tutorials. It offers you a useful way of interpreting the data that’s specific to this book, but that can also be applied to any other data.

Explore the world of Virtual Reality by building immersive and fun VR projects using Unity 3D About This Book Learn the basic principles of virtual reality applications and get to know how they differ from games and desktop apps Build various types of VR experiences, including diorama, first-person characters, riding on rails, 360 degree projections, and social VR A project-based guide that teaches you to use Unity to develop VR applications, which can be experienced with devices such as the Oculus Rift or Google Cardboard Who This Book Is For If you’re a non-programmer unfamiliar with 3D computer graphics, or experienced in both but new to virtual reality, and are interested in building your own VR games or applications then this book is for you. Any experience in Unity is an advantage. What You Will Learn Create 3D scenes with Unity and Blender while learning about world space and scale Build and run VR applications for consumer headsets including Oculus Rift and Google Cardboard Build interactive environments with physics, gravity, animations, and lighting using the Unity engine Experiment with various user interface (UI) techniques that you can use in your VR applications Implement the first-person and third-person experiences that use only head motion gestures for input Create animated walkthroughs, use 360-degree media, and build multi-user social VR experiences Learn about the technology and psychology of VR including rendering, performance and VR motion sickness Gain introductory and advanced experience in Unity programming with the C# language In Detail What is consumer “virtual reality”Wearing a head-mounted display you view stereoscopic 3D scenes. You can look around by moving your head, and walk around using hand controls or motion sensors. You are engaged in a fully immersive experience. On the other hand, Unity is a powerful game development engine that provides a rich set of features such as visual lighting, materials, physics, audio, special effects, and animation for creating 2D and 3D games. Unity 5 has become the leading platform for building virtual reality games, applications and experiences for this new generation of consumer VR devices. Using a practical and project-based approach, this book will educate you about the specifics of virtual reality development in Unity. You will learn how to use Unity to develop VR applications which can be experienced with devices such as the Oculus Rift or Google Cardboard. We will then learn how to engage with virtual worlds from a third person and first person character point of view. Furthermore, you will explore the technical considerations especially important and possibly unique to VR. The projects in the book will demonstrate how to build a variety of VR experiences. You will be diving into the Unity 3D game engine via the interactive Unity Editor as well as C-Sharp programming. By the end of the book, you will be equipped to develop rich, interactive virtual reality experiences using Unity. So, let's get to it! Style and approach This book takes a practical, project-based approach to teach specifics of virtual reality development in Unity. Using a reader-friendly approach, this book will not only provide detailed step-by-step instructions but also discuss the broader context and applications covered within.

Learn effective C++ network programming with Boost.Asio and become a proficient C++ network programmer About This Book Learn efficient C++ network programming with minimum coding using Boost.Asio Your one-stop destination to everything related to the Boost.Asio library Explore the fundamentals of networking to choose designs with more examples, and learn the basics of Boost.Asio Who This Book Is For This book is for C++ Network programmers with basic knowledge of network programming, but no knowledge of how to use Boost.Asio for network programming. What You Will Learn Prepare the tools to simplify network programming in C++ using Boost.Asio Explore the networking concepts of IP addressing, TCP/IP ports and protocols, and LAN topologies Get acquainted with the usage of the Boost libraries Get to know more about the content of Boost.Asio network programming and Asynchronous programming Establish communication between client and server by creating client-server application Understand the various functions inside Boost.Asio C++ libraries to delve into network programming Discover how to debug and run the code successfully In Detail Boost.Asio is a C++ library used for network programming operations. Organizations use Boost because of its productivity. Use of these high-quality libraries speed up initial development, result in fewer bugs, reduce reinvention-of-the-wheel, and cut long-term maintenance costs. Using Boost libraries gives an organization a head start in adopting new technologies. This book will teach you C++ Network programming using synchronous and asynchronous operations in Boost.Asio with minimum code, along with the fundamentals of Boost, server-client applications, debugging, and more. You will begin by preparing and setting up the required tools to simplify your network programming in C++ with Boost.Asio. Then you will learn about the basic concepts in networking such as IP addressing, TCP/IP protocols, and LAN with its topologies. This will be followed by an overview of the Boost libraries and their usage. Next you will get to know more about Boost.Asio and its concepts related to network programming. We will then go on to create a client-server application, helping you to understand the networking concepts. Moving on, you will discover how to use all the functions inside the Boost.Asio C++ libraries. Lastly, you will understand how to debug the code if there are errors found and will run the code successfully. Style and approach An example-oriented book to show you the basics of networking and help you create a network application simply using Boost.Asio, with more examples for you to get up and running with Boost.Asio quickly.

Discover tips and trick for Dynamics NAV report building About This Book Create and customize reports in Dynamics NAV 2015 using RDLC, Word, Power BI, and Reporting Services Work with different elements in the toolbox such as tablix, which can be used as a List, Table, or Matrix and understand the differences between them and when to use which This book is a pragmatic guide with clear instructions and real-world examples to teach you about the reporting capabilities of Dynamics NAV 2015 Who This Book Is For If you are a consultant, developer, customer, user, or just interested in the reporting capabilities of Dynamics NAV, then this book is for you. Basic knowledge of Dynamics NAV will be helpful. What You Will Learn Understand why reports are designed in a specific way and then apply this knowledge to your advantage Develop document reports using different techniques Apply filtering and sorting, and create groups Use RDLC to visualize information Visualize information, KPIs, and trends using expressions, Gauges, Charts, Data bars, Indicators, and Spark lines Create and optimize your dataset for RDLC and for Word layouts Use Power BI with Dynamics NAV to bring your data to life Build Reporting Services reports on top of Dynamics NAV In Detail Microsoft Dynamics NAV is a multi-lingual, multi-currency business management solution that organizations use to manage their accounts, supply chain, sales, payroll, and HR. It is an ERP tool for organizations that is fast to implement, easy to configure, and simple to use. It is widely used because simplicity is a part of its development, product design, usability, and implementation. This book will help you to master, analyze, and deliver the most challenging reporting requirements in Dynamics NAV 2015. The book starts by explaining report development and it's different phases such as data model, layout, and testing you go through. It introduces you to RDLC and the different controls in the toolbox, such as the Tablix, in its many forms. You will learn to use expressions to make your layout dynamic and to overcome typical problems. Moving on, the book will teach you to visualize data and be able to understand and read a report as it is intended. You will also learn to use Microsoft Word to create a layout for a report. With Power BI and Power Pivot, Power View, and Power Map, you will learn how easy and powerful it is to bring your data to life, so you can spot trends and perform in depth analysis of your business. Reporting Services is also explained as another way that you can apply the knowledge you have about RDLC to build RDL layouts outside of Dynamics NAV. By the end, you will create different types of charts so you can visualize key performance indicators inside the Dynamics NAV application. Style and approach This book is an essential guide in to understanding what is involved in creating reports in Dynamics NAV and its reporting capabilities.

Over 50 recipes to help you build dynamic and powerful real-time Java Hibernate applications About This Book Learn to associate JDBC and Hibernate with object persistence Manage association mappings, implement basic annotations and learn caching Get to grips with Hibernate fundamentals from installation to developing a business application with this step-by-step guide Who This Book Is For This is book for Java developers who now want to learn Hibernate. Good knowledge and understanding of Java is preferred to allow efficient programming of the core elements and applications; it would be helpful if readers are familiar with the basics of SQL. What You Will Learn Set up and install Hibernate on your system and explore different ways in which Hibernate can be configured Learn the basic concepts and fundamentals of Java Hibernate Define mappings without a use of XML file using Annotations Persist collection elements such as list, map, set and array Explore the various mapping options and learn to work with Hibernate associations Understand advanced Hibernate concepts such as caching and inheritance Develop an engaging and robust real-world hibernate application based on a common business scenario Integrate Hibernate with other frameworks to develop robust enterprise applications In Detail Hibernate is a database independent technology, so the same code will work for all databases. It helps a Java developer write a query by mapping Java bean to database tables and help create tuned queries that boost performance. Even with limited SQL knowledge one can easily perform database operations. This makes the development faster and more accurate than JDBC. Hibernate supports useful features like connection pooling, caching, and inheritance etc. This book will provide a useful hands-on guide to Hibernate to accomplish the development of a real-time Hibernate application. We will start with the basics of Hibernate, which include setting up Hibernate – the pre-requisites and multiple ways of configuring Hibernate using Java. We will then dive deep into the fundamentals of Hibernate such as SessionFactory, session, criteria, working with objects and criteria. This will help a developer have a better understanding of how Hibernate works and what needs to be done to run a Hibernate application. Moving on, we will learn how to work with annotations, associations and collections. In the final chapters, we will see explore querying, advanced Hibernate concepts and integration with other frameworks. Style and approach This book is a practical guide filled with carefully organized step-by-step instructions. All recipes are arranged in an easy-to understand and clear manner allowing you to apply the solutions to other situations.

Build real-world computer vision applications and develop cool demos using OpenCV for Python About This Book Learn how to apply complex visual effects to images using geometric transformations and image filters Extract features from an image and use them to develop advanced applications Build algorithms to help you understand the image content and perform visual searches Who This Book Is For This book is intended for Python developers who are new to OpenCV and want to develop computer vision applications with OpenCV-Python. This book is also useful for generic software developers who want to deploy computer vision applications on the cloud. It would be helpful to have some familiarity with basic mathematical concepts such as vectors, matrices, and so on. What You Will Learn Apply geometric transformations to images, perform image filtering, and convert an image into a cartoon-like image Detect and track various body parts such as the face, nose, eyes, ears, and mouth Stitch multiple images of a scene together to create a panoramic image Make an object disappear from an image Identify different shapes, segment an image, and track an object in a live video Recognize an object in an image and build a visual search engine Reconstruct a 3D map from images Build an augmented reality application In Detail Computer vision is found everywhere in modern technology. OpenCV for Python enables us to run computer vision algorithms in real time. With the advent of powerful machines, we are getting more processing power to work with. Using this technology, we can seamlessly integrate our computer vision applications into the cloud. Web developers can develop complex applications without having to reinvent the wheel. This book will walk you through all the building blocks needed to build amazing computer vision applications with ease. We start off with applying geometric transformations to images. We then discuss affine and projective transformations and see how we can use them to apply cool geometric effects to photos. We will then cover techniques used for object recognition, 3D reconstruction, stereo imaging, and other computer vision applications. This book will also provide clear examples written in Python to build OpenCV applications. The book starts off with simple beginner’s level tasks such as basic processing and handling images, image mapping, and detecting images. It also covers popular OpenCV libraries with the help of examples. The book is a practical tutorial that covers various examples at different levels, teaching you about the different functions of OpenCV and their actual implementation. Style and approach This is a conversational-style book filled with hands-on examples that are really easy to understand. Each topic is explained very clearly and is followed by a programmatic implementation so that the concept is solidified. Each topic contributes to something bigger in the following chapters, which helps you understand how to piece things together to build something big and complex.