Master the most common algorithms and data structures, and learn how to implement them efficiently using the most up-to-date features of Swift 3 About This Book Develop a deep understanding of the collections in the Swift Standard Library with this step-by-step guide Develop native Swift data structures and algorithms for use in mobile, desktop, and server-based applications Learn about performance efficiency between different data structures and algorithms Who This Book Is For This book is for developers who want to learn how to implement and use common data structures and algorithms natively in Swift. Whether you are a self-taught developer without a formal technical background or you have a degree in Computer Science, this book will provide with the knowledge you need to develop advanced data structures and algorithms in Swift using the latest language features. What You Will Learn Get to know about the basic data structures and how to use the Swift REPL Use the Swift Standard Library collections bridging to Objective-C collections, and find out about protocol-oriented programming Find out about Swift generators and sequences, and see how to use them to implement advanced data structures such as Stack, StackList, Queue, and LinkedList Implement sorting algorithms such as Insertion Sort, Merge Sort, and Quick Sort and understand the performance trade-offs between them See how to implement various binary trees, B-Tree, and Splay Trees Perform advanced searching methods using Red-Black trees, AVL trees, and Trie trees, and take a look at several substring search algorithms Get to know about the data structures used in graphs and how to implement graphs such as depth-first search, breadth-first search, directed graphs, spanning tree, and shortest path Explore algorithm efficiency and see how to measure it In Detail Apple’s Swift language has expressive features that are familiar to those working with modern functional languages, but also provides backward support for Objective-C and Apple’s legacy frameworks. These features are attracting many new developers to start creating applications for OS X and iOS using Swift. Designing an application to scale while processing large amounts of data or provide fast and efficient searching can be complex, especially running on mobile devices with limited memory and bandwidth. Learning about best practices and knowing how to select the best data structure and algorithm in Swift is crucial to the success of your application and will help ensure your application is a success. That’s what this book will teach you. Starting at the beginning, this book will cover the basic data structures and Swift types, and introduce asymptotic analysis. You’ll learn about the standard library collections and bridging between Swift and Objective-C collections. You will see how to implement advanced data structures, sort algorithms, work with trees, advanced searching methods, use graphs, and performance and algorithm efficiency. You’ll also see how to choose the perfect algorithm for your problem. Style and approach This easy-to-follow yet comprehensive guide can either be read from beginning to end, or depending on your current knowledge level, you can jump to the specific chapter that interests you. Each chapter topic starts with an introduction to the topic and algorithm before moving on to the hands-on implementation and analysis.

Learn everything you need to manage and handle your systems with ease with Ansible 2 using this comprehensive guide About This Book Simplify the automation of applications and systems using the newest version of Ansible Get acquainted with fundamentals of Ansible such as playbooks, modules, and various testing strategies A comprehensive, learning guide that provides you with great skills to automate your organization’s infrastructure using Ansible 2 Who This Book Is For The book is for sys admins who want to automate their organization’s infrastructure using Ansible 2. No prior knowledge of Ansible is required. What You Will Learn Set up Ansible 2 and an Ansible 2 project in a future-proof way Perform basic operations with Ansible 2 such as creating, copying, moving, changing, and deleting files, and creating and deleting users Deploy complete cloud environments using Ansible 2 on AWS and DigitalOcean Explore complex operations with Ansible 2 (Ansible vault, e-mails, and Nagios) Develop and test Ansible playbooks Write a custom module and test it In Detail Ansible is an open source automation platform that assists organizations with tasks such as configuration management, application deployment, orchestration, and task automation. With Ansible, even complex tasks can be handled easier than before. In this book, you will learn about the fundamentals and practical aspects of Ansible 2 by diving deeply into topics such as installation (Linux, BSD, and Windows Support), playbooks, modules, various testing strategies, provisioning, deployment, and orchestration. In this book, you will get accustomed with the new features of Ansible 2 such as cleaner architecture, task blocks, playbook parsing, new execution strategy plugins, and modules. You will also learn how to integrate Ansible with cloud platforms such as AWS. The book ends with the enterprise versions of Ansible, Ansible Tower and Ansible Galaxy, where you will learn to interact Ansible with different OSes to speed up your work to previously unseen levels By the end of the book, you’ll able to leverage the Ansible parameters to create expeditious tasks for your organization by implementing the Ansible 2 techniques and paradigms. Style and approach This book is a step-by-step learning guide on the all new Ansible 2, which is an ideal configuration management tool.

Leverage the power of Julia to design and develop high performing programs About This Book Get to know the best techniques to create blazingly fast programs with Julia Stand out from the crowd by developing code that runs faster than your peers' code Complete an extensive data science project through the entire cycle from ETL to analytics and data visualization Who This Book Is For This learning path is for data scientists and for all those who work in technical and scientific computation projects. It will be great for Julia developers who are interested in high-performance technical computing. This learning path assumes that you already have some basic working knowledge of Julia's syntax and high-level dynamic languages such as MATLAB, R, Python, or Ruby. What You Will Learn Set up your Julia environment to achieve the highest productivity Solve your tasks in a high-level dynamic language and use types for your data only when needed Apply Julia to tackle problems concurrently and in a distributed environment Get a sense of the possibilities and limitations of Julia's performance Use Julia arrays to write high performance code Build a data science project through the entire cycle of ETL, analytics, and data visualization Display graphics and visualizations to carry out modeling and simulation in Julia Develop your own packages and contribute to the Julia Community In Detail In this learning path, you will learn to use an interesting and dynamic programming language—Julia! You will get a chance to tackle your numerical and data problems with Julia. You’ll begin the journey by setting up a running Julia platform before exploring its various built-in types. We’ll then move on to the various functions and constructs in Julia. We’ll walk through the two important collection types—arrays and matrices in Julia. You will dive into how Julia uses type information to achieve its performance goals, and how to use multiple dispatch to help the compiler emit high performance machine code. You will see how Julia’s design makes code fast, and you’ll see its distributed computing capabilities. By the end of this learning path, you will see how data works using simple statistics and analytics, and you’ll discover its high and dynamic performance—its real strength, which makes it particularly useful in highly intensive computing tasks. This learning path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Getting Started with Julia by Ivo Balvaert Julia High Performance by Avik Sengupta Mastering Julia by Malcolm Sherrington Style and approach This hands-on manual will give you great explanations of the important concepts related to Julia programming.

Unleash the power and flexibility of the Bayesian framework About This Book Simplify the Bayes process for solving complex statistical problems using Python; Tutorial guide that will take the you through the journey of Bayesian analysis with the help of sample problems and practice exercises; Learn how and when to use Bayesian analysis in your applications with this guide. Who This Book Is For Students, researchers and data scientists who wish to learn Bayesian data analysis with Python and implement probabilistic models in their day to day projects. Programming experience with Python is essential. No previous statistical knowledge is assumed. What You Will Learn Understand the essentials Bayesian concepts from a practical point of view Learn how to build probabilistic models using the Python library PyMC3 Acquire the skills to sanity-check your models and modify them if necessary Add structure to your models and get the advantages of hierarchical models Find out how different models can be used to answer different data analysis questions When in doubt, learn to choose between alternative models. Predict continuous target outcomes using regression analysis or assign classes using logistic and softmax regression. Learn how to think probabilistically and unleash the power and flexibility of the Bayesian framework In Detail The purpose of this book is to teach the main concepts of Bayesian data analysis. We will learn how to effectively use PyMC3, a Python library for probabilistic programming, to perform Bayesian parameter estimation, to check models and validate them. This book begins presenting the key concepts of the Bayesian framework and the main advantages of this approach from a practical point of view. Moving on, we will explore the power and flexibility of generalized linear models and how to adapt them to a wide array of problems, including regression and classification. We will also look into mixture models and clustering data, and we will finish with advanced topics like non-parametrics models and Gaussian processes. With the help of Python and PyMC3 you will learn to implement, check and expand Bayesian models to solve data analysis problems. Style and approach Bayes algorithms are widely used in statistics, machine learning, artificial intelligence, and data mining. This will be a practical guide allowing the readers to use Bayesian methods for statistical modelling and analysis using Python.

Over 30 life-changing recipes to help you create cutting edge, hybrid apps with Ionic 2 About This Book Leverage Ionic 2 and its exciting new features to create cutting edge real-time apps Work through simple recipes to address your problems directly and solve them effectively Get examples at each step to guide you on your learning curve Who This Book Is For This book is for front end JavaScript developers who know the basics of JavaScript programming. No prior knowledge of Ionic is required to get the most of this book. What You Will Learn Create custom UIs using Angular 2 directives Make the best use of REST APIs to submit forms Create beautiful animations and graphics in the application Embed videos and other media into the app Access native device functionalities such as a camera and maps using ngCordova Theme the application based on the various platform styles available Publish your application to a variety of platforms Leverage Angular 2 events and Ionic-specific events to communicate In Detail Developing real-time apps is the need of the hour, and apps that deal with humongous amounts of user data and real-time information that needs to be updated frequently are in high demand. Currently, one of the most popular frameworks for this task is Ionic Framework, which is undergoing a major makeover. This book will get you started with Ionic and help you create Angular 2 components that interact with templates. From there, you’ll work with Ionic components and find out how to share data efficiently between them. You’ll discover how to make the best use of the REST API to handle back-end services and then move on to animating the application to make it look pretty. You’ll learn to add in a local push notification in order to test the app. You’ll work with Cordova to support native functionalities on both iOS and Android. From there, you’ll get to grips with using the default themes for each platform as well as customizing your own. Finally, you’ll see how best to deploy your app to different platforms. This book will solve all your Ionic-related issues through dedicated recipes that will help you get the best out of Ionic. Style and approach This book is a recipe-based solution to all your Ionic 2 related problems and will help you create cutting edge real-time apps with ease through simple-to-understand step-by-step recipes.

Master Phalcon by implementing hands-on recipes using industry best practices with the Web and CLI interfaces About This Book Create quick prototypes with the Phalcon Developer Tools Learn to use the powerful and uniquely efficient Phalcon ORM Reuse codes in real projects Who This Book Is For If you are a beginner-to-intermediate Phalcon developer who wants to level up or an advanced user who is seeking some new techniques and insight, then this book is perfect for you. This book will be relevant to you over a long period of time due to the mixed nature of this book in providing both abstract comprehension as well as specific examples meant to be usable in your projects. You will be able to experiment with each new aspect of integration in prebuilt recipes meant to best illustrate each specific feature. This will save you lots of time getting up to speed before attempting to integrate into a real application. What You Will Learn Install the Phalcon extension from both premade packages and source code Create a normal and micro application structure Understand the dispatcher event cycle and create custom plugins Get hands-on using the Phalcon Query Language and ORM Create flexible views with the Volt template system Leverage Phalcon to prevent common security vulnerabilities Optimize an application with focused solutions Profile and debug an application to get increased reliability In Detail Phalcon is a high-performance PHP framework delivered as a PHP extension. This provides new opportunities for speed and application design, which until recently have been unrealized in the PHP ecosystem. Packed with simple learning exercises, technology prototypes, and real-world usable code, this book will guide you from the beginner and setup stage all the way to advanced usage. You will learn how to avoid niche pitfalls, how to use the command-line developer tools, how to integrate with new web standards, as well as how to set up and customize the MVC application structure. You will see how Phalcon can be used to quickly set up a single file web application as well as a complex multi-module application suitable for long-term projects. Some of the recipes focus on abstract concepts that are vital to get a deep comprehension of Phalcon and others are designed as a vehicle to deliver real-world usable classes and code snippets to solve advanced problems. You’ll start out with basic setup and application structure and then move onto the Phalcon MVC and routing implementation, the power of the ORM and Phalcon Query Language, and Phalcon’s own Volt templating system. Finally, you will move on to caching, security, and optimization. Style and approach An easy-to-start guide that provides

Get the most out of the Elastic Stack for various complex analytics using this comprehensive and practical guide About This Book Your one-stop solution to perform advanced analytics with Elasticsearch, Logstash, and Kibana Learn how to make better sense of your data by searching, analyzing, and logging data in a systematic way This highly practical guide takes you through an advanced implementation on the ELK stack in your enterprise environment Who This Book Is For This book cater to developers using the Elastic stack in their day-to-day work who are familiar with the basics of Elasticsearch, Logstash, and Kibana, and now want to become an expert at using the Elastic stack for data analytics. What You Will Learn Build a pipeline with help of Logstash and Beats to visualize Elasticsearch data in Kibana Use Beats to ship any type of data to the Elastic stack Understand Elasticsearch APIs, modules, and other advanced concepts Explore Logstash and it’s plugins Discover how to utilize the new Kibana UI for advanced analytics See how to work with the Elastic Stack using other advanced configurations Customize the Elastic Stack and plugin development for each of the component Work with the Elastic Stack in a production environment Explore the various components of X-Pack in detail. In Detail Even structured data is useless if it can’t help you to take strategic decisions and improve existing system. If you love to play with data, or your job requires you to process custom log formats, design a scalable analysis system, and manage logs to do real-time data analysis, this book is your one-stop solution. By combining the massively popular Elasticsearch, Logstash, Beats, and Kibana, elastic.co has advanced the end-to-end stack that delivers actionable insights in real time from almost any type of structured or unstructured data source. If your job requires you to process custom log formats, design a scalable analysis system, explore a variety of data, and manage logs, this book is your one-stop solution. You will learn how to create real-time dashboards and how to manage the life cycle of logs in detail through real-life scenarios. This book brushes up your basic knowledge on implementing the Elastic Stack and then dives deeper into complex and advanced implementations of the Elastic Stack. We’ll help you to solve data analytics challenges using the Elastic Stack and provide practical steps on centralized logging and real-time analytics with the Elastic Stack in production. You will get to grip with advanced techniques for log analysis and visualization. Newly announced features such as Beats and X-Pack are also covered in detail with examples. Toward the end, you will see how to use the Elastic stack for real-world case studies and we’ll show you some best practices and troubleshooting techniques for the Elastic Stack. Style and approach This practical guide shows you how to perform advanced analytics with the Elastic stack through real-world use cases. It includes common and some not so common scenarios to use the Elastic stack for data analysis.

Take charge of SaltStack to automate and configure your enterprise-grade environments About This Book Automate tasks effectively and take charge of your infrastructure Effectively scale Salt to manage thousands of machines and tackle everyday problems Explore Salt’s inner workings and advance your knowledge of it Who This Book Is For This book is ideal for IT professionals and ops engineers who already manage groups of servers, but would like to expand their knowledge and gain expertise with SaltStack. This book explains the advanced features and concepts of Salt. A basic knowledge of Salt is required in order to get to grips with advanced Salt features. What You Will Learn Automate tasks effectively, so that your infrastructure can run itself Start building more complex concepts Master user-level internals Build scaling strategies Explore monitoring strategies Learn how to troubleshoot Salt and its subcomponents Explore best practices for Salt In Detail SaltStack is a powerful configuration management and automation suite designed to manage servers and tens of thousands of nodes. This book showcases Salt as a very powerful automation framework. We will review the fundamental concepts to get you in the right frame of mind, and then explore Salt in much greater depth. You will explore Salt SSH as a powerful tool and take Salt Cloud to the next level. Next, you’ll master using Salt services with ease in your infrastructure. You will discover methods and strategies to scale your infrastructure properly. You will also learn how to use Salt as a powerful monitoring tool. By the end of this book, you will have learned troubleshooting tips and best practices to make the entire process of using Salt pain-free and easy. Style and approach This book follows a step-by-step conversational tone. Topics are covered in detail through examples and a user-friendly approach.

Create interactive cross-platform reports and dashboards using SQL Server 2016 Reporting Services About This Book Get up to speed with the newly-introduced enhancements and the more advanced query and reporting features Easily access your important data by creating visually appealing dashboards in the Power BI practical recipe Create cross-browser and cross-platform reports using SQL Server 2016 Reporting Services Who This Book Is For This book is for software professionals who develop and implement reporting solutions using Microsoft SQL Server. It is especially relevant for professionals who are software engineers, software architects, DW/BI engineers, and DW/BI architects who perform simple to complex report authoring implementations. This book is also suitable for those who develop software solutions that integrate reporting solutions and are keen to learn about Microsoft SQL Server 2016’s features and capabilities. What You Will Learn Key capabilities, architecture, and components of Reporting Services New features that have been added to Reporting Services Design the architecture for reporting solutions Design the architecture for BI solutions Implement reporting solutions using Reporting Services Improve the performance, availability, and scalability of the reporting solution Enhance reporting solutions with custom programming and improved security In Detail Microsoft SQL Server 2016 Reporting Services comes with many new features. It offers different types of reporting such as Production, Ad-hoc, Dashboard, Mash-up, and Analytical. SQL Server 2016 also has a surfeit of new features including Mobile Reporting, and Power BI integration. This book contains recipes that explore the new and advanced features added to SQL Server 2016. The first few chapters cover recipes on configuring components and how to explore these new features. You’ll learn to build your own reporting solution with data tools and report builder, along with learning techniques to create visually appealing reports. This book also has recipes for enhanced mobile reporting solutions, accessing these solutions effectively, and delivering interactive business intelligence solutions. Towards the end of the book, you’ll get to grips with running reporting services in SharePoint integrated mode and be able to administer, monitor, and secure your reporting solution. This book covers about the new offerings of Microsoft SQL Server 2016 Reporting Services in comprehensive detail and uses examples of real-world problem-solving business scenarios. Style and approach This comprehensive cookbook follows a problem-solution approach to help you overcome any obstacle when creating interactive, visually-appealing reports using SQL Server 2016 Reporting Services. Each recipe focuses on a specific task and is written in a clear, solution-focused style.

Bring the power of functional programming to Swift to develop clean, smart, scalable and reliable applications. About This Book ?Written for the latest version of Swift, this is a comprehensive guide that introduces iOS, Web and macOS developers to the all-new world of functional programming that has so far been alien to them ?Get familiar with using functional programming alongside existing OOP techniques so you can get the best of both worlds and develop clean, robust, and scalable code ?Develop a case study on example backend API with Swift and Vapor Framework and an iOS application with Functional Programming, Protocol-Oriented Programming, Functional Reactive Programming, and Object-Oriented Programming techniques Who This Book Is For Meant for a reader who knows object-oriented programming, has some experience with Objective-C/Swift programming languages and wants to further enhance his skills with functional programming techniques with Swift 3.x. What You Will Learn ?Understand what functional programming is and why it matters ?Understand custom operators, function composition, currying, recursion, and memoization ?Explore algebraic data types, pattern matching, generics, associated type protocols, and type erasure ?Get acquainted with higher-kinded types and higher-order functions using practical examples ?Get familiar with functional and non-functional ways to deal with optionals ?Make use of functional data structures such as semigroup, monoid, binary search tree, linked list, stack, and lazy list ?Understand the importance of immutability, copy constructors, and lenses

This book starts by introducing you to supervised learning algorithms such as simple linear regression, the classical multilayer perceptron and more sophisticated deep convolutional networks. You will also explore image processing with recognition of hand written digit images, classification of images into different categories, and advanced objects recognition with related image annotations. An example of identification of salient points for face detection is also provided. Next you will be introduced to Recurrent Networks, which are optimized for processing sequence data such as text, audio or time series. Following that, you will learn about unsupervised learning algorithms such as Autoencoders and the very popular Generative Adversarial Networks (GAN). You will also explore non-traditional uses of neural networks as Style Transfer. Finally, you will look at Reinforcement Learning and its application to AI game playing, another popular direction of research and application of neural networks. What you will learn ?Optimize step-by-step functions on a large neural network using the Backpropagation Algorithm ?Fine-tune a neural network to improve the quality of results ?Use deep learning for image and audio processing ?Use Recursive Neural Tensor Networks (RNTNs) to outperform standard word embedding in special cases ?Identify problems

Customize your NAV applications About This Book ?Gain from the insights and methods of industry-leading experts and tailor your applications to best suit the needs of your business ?Learn through the detailed explanations and useful examples that are presented in a logical, step-by-step manner ?This comprehensive guide is written with the goals of being used as a classroom text, a self-study text, and as a handy in-depth reference guide Who This Book Is For This book will appeal to all those who want to learn about NAV's powerful and extensive built-in development capabilities. It assumes that you understand programming and are familiar with business application software, although you aren't expected to have worked with NAV before. ERP consultants and managers of NAV development will also find the book helpful. What You Will Learn ?Productively and effectively use the development tools that are built into Dynamics NAV ?Understand the strengths of NAV's development tools and how they can be applied to address functional business requirements ?Introduction to programming using the C/AL language in the C/SIDE Development Environment ?Explore functional design and development using C/AL ?Leverage advanced NAV development features and tools ?Get to know the best practices to design and develop modifications of new functionality integrated with the standard NAV software In Detail Microsoft Dynamics NAV is a full business solution suite, and a complete ERP solution, which contains a robust set of development tools to support customization and enhancement. These

"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. "

"Key Features ?Get to the grips with the latest version of Apache Spark ?Utilize Spark's machine learning library to implement predictive analytics ?Leverage Spark's powerful tools to load, analyze, clean, and transform your data Book De*ion Spark ML is the machine learning module of Spark. It uses in-memory RDDs to process machine learning models faster for clustering, classification, and regression. This book will teach you about popular machine learning algorithms and their implementation. You will learn how various machine learning concepts are implemented in the context of Spark ML. You will start by installing Spark in a single and multinode cluster. Next you'll see how to execute Scala and Python based programs for Spark ML. Then we will take a few datasets and go deeper into clustering, classification, and regression. Toward the end, we will also cover text processing using Spark ML. Once you have learned the concepts, they can be applied to implement algorithms in either green-field implementations or to migrate existing systems to this new platform. You can migrate from Mahout or Scikit to use Spark ML. What you will learn ?Get hands-on with the latest version of Spark ML ?Create your first Spark program with Scala and Python ?Set up and configure a development environment for Spark on your own computer, as well as on Amazon EC2 ?Access public machine learning datasets and use Spark to load, process, clean, and transform data ?Use Spark's machine learning library to implement programs by utilizing well-known machine learning models ?Deal with large-scale text data, including feature extraction and using text data as input to your machine learning models ?Write Spark functions to evaluate the performance of your machine learning models "

Machine learning has become the new black. The challenge in today's world is the explosion of data from existing legacy data and incoming new structured and unstructured data. The complexity of discovering, understanding, performing analysis, and predicting outcomes on the data using machine learning algorithms is a challenge. This cookbook will help solve everyday challenges you face as a data scientist. The application of various data science techniques and on multiple data sets based on real-world challenges you face will help you appreciate a variety of techniques used in various situations. The first half of the book provides recipes on fairly complex machine-learning systems, where you'll learn to explore new areas of applications of machine learning and improve its efficiency. That includes recipes on classifications, neural networks, unsupervised and supervised learning, deep learning, reinforcement learning, and more. The second half of the book focuses on three different machine learning case studies, all based on real-world data, and offers solutions and solves specific machine-learning issues in each one. What You Will Learn ?Get equipped with a deeper understanding of how to apply machine-learning techniques ?Implement each of the advanced machine-learning techniques ?Solve real-life problems that are encountered in order to make your applications produce improved results ?Gain hands-on experience in problem solving for your machine-learning systems ?Understand the methods of collecting data, preparing data for usage, training the model, evaluating the model's performance, and improving the model's performance

comprehensive guide from Oracle experts, that will act as your single point of reference for building an Oracle BI 12c system that turns data in actionable insight. About This Book ?Come, start your first Oracle Business intelligence system and excel in BI with this exhaustive guide ?An all-encompassing guide for your Oracle business intelligence needs ?Learn from the self-paced professional guidance and implement Oracle business intelligence using this easy-to-follow guide by our experts Who This Book Is For If your job includes working on data, improving the financial or operational performance of your organization or you are a consultant for the above, then this book is for you. If you have been placed on a business intelligence project, then this book is for you. If you are the Project Manager, Business Analyst or Data Scientist then this book is for you. If you are an end user of Oracle Business Intelligence, then this book is for you too. Having a basic understanding of databases and the use of Business Intelligence is expected, but no knowledge of Oracle BI is required. What You Will Learn ?Install OBIEE in Windows, including how to create the underlying Weblogic Application server and the required database ?Build the BI system repository, the vital engine connecting your data to the front end of Oracle BI ?Develop effective analysis, draw out meaning from the data, and present it to end users on interactive dashboards ?Build pixel-perfect, printable reports using the embedded BI Publisher feature ?Build agents for actionable insight and enable your users to act on Business Intelligence at their desktop or

Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of this comprehensive TensorFlow guide About This Book ?Learn how to implement advanced techniques in deep learning with Google's brainchild, TensorFlow ?Explore deep neural networks and layers of data abstraction with the help of this comprehensive guide ?Real-world contextualization through some deep learning problems concerning research and application Who This Book Is For The book is intended for a general audience of people interested in machine learning and machine intelligence. A rudimentary level of programming in one language is assumed, as is a basic familiarity with computer science techniques and technologies, including a basic awareness of computer hardware and algorithms. Some competence in mathematics is needed to the level of elementary linear algebra and calculus. What You Will Learn ?Learn about machine learning landscapes along with the historical development and progress of deep learning ?Learn about deep machine intelligence and GPU computing with the latest TensorFlow 1.x ?Access public datasets and utilize them using TensorFlow to load, process, and transform data ?Use TensorFlow on real-world datasets, including images, text, and more ?Learn how to evaluate the performance of your deep learning models ?Using deep learning for scalable object detection and mobile computing ?Train machines quickly to learn from data by exploring reinforcement learning techniques ?Explore active areas of deep learning research and applications

React Native's ability to build performant mobile applications with JavaScript has resulted in its popularity amongst developers. Developers now have the luxury to create incredible mobile experiences that look and feel native to their platforms with the comfort of a well-known language and the popular React.js library. This book will show you how to build your own native mobile applications for the iOS and Android platforms while leveraging the finesse and simplicity of JavaScript and React. Throughout the book you will build three projects, each of increasing complexity. You will also link up with the third-party Facebook SDK, convert an app to support the Redux architecture, and learn the process involved in making your apps available for sale on the iOS App Store and Google Play. At the end of this book, you will have learned and implemented a wide breadth of core APIs and components found in the React Native framework that are necessary in creating great mobile experiences. What you will learn ?How to create mobile-performant iOS and Android apps using JavaScript and React ?The potential of each API and component, putting them into practice throughout the course of three projects ?The process of integrating the Facebook SDK to build an app that connects to third-party data ?Every step taken to implement Redux, a popular state management library, in your mobile apps

Do you want to make sense of your data? Do you want to create interactive charts, data trees, info-graphics, geospatial charts, and maps efficiently? This book is your ideal choice to master interactive data visualization with D3.js V4. The book includes a number of extensive examples that to help you hone your skills with data visualization. Throughout nine chapters these examples will help you acquire a clear practical understanding of the various techniques, tools and functionality provided by D3.js. You will first setup your D3.JS development environment and learn the basic patterns needed to visualize your data. After that you will learn techniques to optimize different processes such as working with selections; animating data transitions; creating graps and charts, integrating external resources (static as well as streaming); visualizing information on maps; working with colors and scales; utilizing the different D3.js APIs; and much more. The book will also guide you through creating custom graphs and visualizations, and show you how to go from the raw data to beautiful visualizations. The extensive examples will include working with complex and realtime data streams, such as seismic data, geospatial data, scientific data, and more. Towards the end of the book, you will learn to add more functionality on top of D3.js by using it with other external libraries and integrating it with Ecma* 6 and Type*

Bluetooth Low Energy (BLE) is a Wireless Personal Area network technology aimed at novel applications for smart devices. High-tech BLE profiles and services are being increasingly used by application developers and hardware enthusiasts to allow devices to interact with the surrounding world. This book will focus on a technical introduction to BLE and how it is reshaping small-distance communication. We will start with IoT, where many technologies such as BLE, Zigbee, and IEEE 802.15.4 Mesh will be introduced. The book will present BLE from an engineering perspective, from which the protocol stack, architecture, and layers are discussed. You will learn to implement customized projects for Peripheral/Central communication, BLE Beacons, indoor navigation using triangulation, and the Internet gateway for Bluetooth Low Energy Personal Network, all using various code samples and APIs on Android, iOS, and the Web. Finally, the book will conclude with a glimpse into future technologies destined to be prominent in years to come. What you will learn ?Bluetooth Low Energy in theory. ?Bluetooth Low Energy Hardware and Software Development Kits. ?Implement Bluetooth low energy communication (central and peripheral) using Android. ?Master BLE Beacons with examples implemented over Eddystone and iBeacons.

Writing concurrent and parallel programming applications is an integral skill for any Java programmer. Java 9 comes with a host of fantastic features, including significant performance improvements and new APIs. This book will take you through all the new APIs, showing you how to build parallel and multi-threaded applications. The book covers all the elements of the Java Concurrency API, with essential recipes that will help you take advantage of the exciting new capabilities. You will learn how to use parallel and reactive streams to process massive data sets. Next, you will move on to create streams and use all their intermediate and terminal operations to process big collections of data in a parallel and functional way. Further, you ll discover a whole range of recipes for almost everything, such as thread management, synchronization, executors, parallel and reactive streams, and many more. At the end of the book, you will learn how to obtain information about the status of some of the most useful components of the Java Concurrency API and how to test concurrent applications using different tools. What you will learn ?Find out to manage the basic components of the Java Concurrency API ?Use synchronization mechanisms to avoid data race conditions and other problems of concurrent applications ?Separate the thread management from the rest of the application with the Executor framework ?Solve problems using a parallelized version of the divide and conquer paradigm with the Fork / Join framework ?Process massive data sets in an optimized way using streams and reactive streams ?See which data structures we can use in concurrent applications and how to use them ?Practice efficient techniques to test concurrent applications ?Get to know tips and tricks to design concurrent applications