Exploit the features of TypeScript to easily create your very own web applications About This Book ? Develop modular, scalable, maintainable, and adaptable web applications by taking advantage of TypeScript ? Walk through the fundamentals of TypeScript with the help of practical examples ? Enhance your web development skills using TypeScript 2.x Who This Book Is For If you are a developer aiming to learn TypeScript to build attractive web applications, this book is for you. No prior knowledge of TypeScript is required. However, a basic understanding of JavaScript would be an added advantage. What You Will Learn ? Understand TypeScript in depth, including its runtime and advanced type system features ? Master the core principles of the object-oriented programming and functional programming paradigms with TypeScript ? Save time using automation tools such as Gulp, Webpack, ts-node, and npm scripts ? Develop robust, modular, scalable, maintainable, and adaptable applications with testing frameworks such as Mocha, Chai, and Sinon.JS ? Put your TypeScript skills to practice by developing full-stack web applications with Node.js, React and Angular ? Use the APIs of the TypeScript compiler to build custom code analysis tool In Detail TypeScript is an open source and cross-platform statically typed superset of JavaScript that compiles to plain JavaScript and runs in any browser or host. This book is a step-by-step guide that will take you through the use and benefits of TypeScript with the help of practical examples. You will start off by understanding the basics as well as the new features of TypeScript 2.x. Then, you will learn how to work with functions and asynchronous programming APIs. You will continue by learning how to resolve runtime issues and how to implement TypeScript applications using the Object-oriented programming (OOP) and functional programming (FP) paradigms. Later, you will automate your development workflow with the help of tools such as Webpack. Towards the end of this book, you will delve into some real-world scenarios by implementing some full-stack TypeScript applications with Node.js, React and Angular as well as how to optimize and test them. Finally, you will be introduced to the internal APIs of the TypeScript compiler, and you will learn how to create custom code analysis tools. Style and approach This is a step-by-step guide that covers the fundamentals of TypeScript with practical examples.

Leverage the power of the Reinforcement Learning techniques to develop self-learning systems using Tensorflow About This Book ? Learn reinforcement learning concepts and their implementation using TensorFlow ? Discover different problem-solving methods for Reinforcement Learning ? Apply reinforcement learning for autonomous driving cars, robobrokers, and more Who This Book Is For If you want to get started with reinforcement learning using TensorFlow in the most practical way, this book will be a useful resource. The book assumes prior knowledge of machine learning and neural network programming concepts, as well as some understanding of the TensorFlow framework. No previous experience with Reinforcement Learning is required. What You Will Learn ? Implement state-of-the-art Reinforcement Learning algorithms from the basics ? Discover various techniques of Reinforcement Learning such as MDP, Q Learning and more ? Learn the applications of Reinforcement Learning in advertisement, image processing, and NLP ? Teach a Reinforcement Learning model to play a game using TensorFlow and the OpenAI gym ? Understand how Reinforcement Learning Applications are used in robotics In Detail Reinforcement Learning (RL), allows you to develop smart, quick and self-learning systems in your business surroundings. It is an effective method to train your learning agents and solve a variety of problems in Artificial Intelligence—from games, self-driving cars and robots to enterprise applications that range from datacenter energy saving (cooling data centers) to smart warehousing solutions. The book covers the major advancements and successes achieved in deep reinforcement learning by synergizing deep neural network architectures with reinforcement learning. The book also introduces readers to the concept of Reinforcement Learning, its advantages and why it’s gaining so much popularity. The book also discusses on MDPs, Monte Carlo tree searches, dynamic programming such as policy and value iteration, temporal difference learning such as Q-learning and SARSA. You will use TensorFlow and OpenAI Gym to build simple neural network models that learn from their own actions. You will also see how reinforcement learning algorithms play a role in games, image processing and NLP. By the end of this book, you will have a firm understanding of what reinforcement learning is and how to put your knowledge to practical use by leveraging the power of TensorFlow and OpenAI Gym. Style and approach An Easy-to-follow, step-by-step guide to help you get to grips with real-world applications of Reinforcement Learning with TensorFlow.

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.

Unleash the data processing and analytics capability of Apache Spark with the language of choice: Java About This Book ? Perform big data processing with Spark—without having to learn Scala! ? Use the Spark Java API to implement efficient enterprise-grade applications for data processing and analytics ? Go beyond mainstream data processing by adding querying capability, Machine Learning, and graph processing using Spark Who This Book Is For If you are a Java developer interested in learning to use the popular Apache Spark framework, this book is the resource you need to get started. Apache Spark developers who are looking to build enterprise-grade applications in Java will also find this book very useful. What You Will Learn ? Process data using different file formats such as XML, JSON, CSV, and plain and delimited text, using the Spark core Library. ? Perform analytics on data from various data sources such as Kafka, and Flume using Spark Streaming Library ? Learn SQL schema creation and the analysis of structured data using various SQL functions including Windowing functions in the Spark SQL Library ? Explore Spark Mlib APIs while implementing Machine Learning techniques to solve real-world problems ? Get to know Spark GraphX so you understand various graph-based analytics that can be performed with Spark In Detail Apache Spark is the buzzword in the big data industry right now, especially with the increasing need for real-time streaming and data processing. While Spark is built on Scala, the Spark Java API exposes all the Spark features available in the Scala version for Java developers. This book will show you how you can implement various functionalities of the Apache Spark framework in Java, without stepping out of your comfort zone. The book starts with an introduction to the Apache Spark 2.x ecosystem, followed by explaining how to install and configure Spark, and refreshes the Java concepts that will be useful to you when consuming Apache Spark's APIs. You will explore RDD and its associated common Action and Transformation Java APIs, set up a production-like clustered environment, and work with Spark SQL. Moving on, you will perform near-real-time processing with Spark streaming, Machine Learning analytics with Spark MLlib, and graph processing with GraphX, all using various Java packages. By the end of the book, you will have a solid foundation in implementing components in the Spark framework in Java to build fast, real-time applications. Style and approach This practical guide teaches readers the fundamentals of the Apache Spark framework and how to implement components using the Java language. It is a unique blend of theory and practical examples, and is written in a way that will gradually build your knowledge of Apache Spark.

Over 60 high-quality recipes covering debugging, security, performance, microservices, web frameworks, databases, deployment and more; rewritten for Node 4, 6, and 8. About This Book ? Security between Node.js and browser applications explained and applied in depth ? Cutting edge techniques and tools for measuring and improving performance ? Contemporary techniques to create developer-ergonomic, readily-scalable production systems Who This Book Is For If you have good knowledge of JavaScript and want to build fast, efficient, scalable client-server solutions, then this book is for you. Some experience with Node.js is assumed to get the most out of this book. If working from a beginner level Node Cookbook 2nd Edition is recommended as a primer for Node Cookbook 3rd Edition. What You Will Learn ? Rapidly become proficient at debugging Node.js programs ? Write and publish your own Node.js modules ? Become deeply acquainted with Node.js core API’s ? Use web frameworks such as Express, Hapi and Koa for accelerated web application development ? Apply Node.js streams for low-footprint infinite-capacity data processing ? Fast-track performance knowledge and optimization abilities ? Compare and contrast various persistence strategies, including database integrations with MongoDB, MySQL/MariaDB, Postgres, Redis, and LevelDB ? Grasp and apply critically essential security concepts ? Understand how to use Node with best-of-breed deployment technologies: Docker, Kubernetes and AWS In Detail The principles of asynchronous event-driven programming are perfect for today's web, where efficient real-time applications and scalability are at the forefront. Server-side JavaScript has been here since the 90s but Node got it right. This edition is a complete rewrite of the original, and is targeted against Node 4, 6, and 8. It shows you how to build fast, efficient, and scalable client-server solutions using the latest versions of Node. Beginning with adopting debugging tips and tricks of the trade and learning how to write your own modules, then covering the fundamentals of streams in Node.js, you will go on to discover I/O control, implementation of various web protocols, you’ll work up to integrating with cross-section of databases such as MongoDB, MySQL/MariaDB, Postgres, Redis, and LevelDB and building web application with Express, Hapi and Koa. You will then learn about security essentials in Node.js and the advanced optimization tools and techniques By the end of the book you should have acquired a level of proficiency that allows you to confidently build a full production-ready and scalable Node.js system. Style and approach This recipe-based practical guide presents each topic with step-by-step instructions on how you can create fast and efficient server side applications using the latest features and capabilities in Node 8 whilst also supporting usage with Node 4 and 6.

Expand your OpenCV knowledge and master key concepts of machine learning using this practical, hands-on guide. About This Book ? Load, store, edit, and visualize data using OpenCV and Python ? Grasp the fundamental concepts of classification, regression, and clustering ? Understand, perform, and experiment with machine learning techniques using this easy-to-follow guide ? Evaluate, compare, and choose the right algorithm for any task Who This Book Is For This book targets Python programmers who are already familiar with OpenCV; this book will give you the tools and understanding required to build your own machine learning systems, tailored to practical real-world tasks. What You Will Learn ? Explore and make effective use of OpenCV's machine learning module ? Learn deep learning for computer vision with Python ? Master linear regression and regularization techniques ? Classify objects such as flower species, handwritten digits, and pedestrians ? Explore the effective use of support vector machines, boosted decision trees, and random forests ? Get acquainted with neural networks and Deep Learning to address real-world problems ? Discover hidden structures in your data using k-means clustering ? Get to grips with data pre-processing and feature engineering In Detail Machine learning is no longer just a buzzword, it is all around us: from protecting your email, to automatically tagging friends in pictures, to predicting what movies you like. Computer vision is one of today's most exciting application fields of machine learning, with Deep Learning driving innovative systems such as self-driving cars and Google’s DeepMind. OpenCV lies at the intersection of these topics, providing a comprehensive open-source library for classic as well as state-of-the-art computer vision and machine learning algorithms. In combination with Python Anaconda, you will have access to all the open-source computing libraries you could possibly ask for. Machine learning for OpenCV begins by introducing you to the essential concepts of statistical learning, such as classification and regression. Once all the basics are covered, you will start exploring various algorithms such as decision trees, support vector machines, and Bayesian networks, and learn how to combine them with other OpenCV functionality. As the book progresses, so will your machine learning skills, until you are ready to take on today's hottest topic in the field: Deep Learning. By the end of this book, you will be ready to take on your own machine learning problems, either by building on the existing source code or developing your own algorithm from scratch! Style and approach OpenCV machine learning connects the fundamental theoretical principles behind machine learning to their practical applications in a way that focuses on asking and answering the right questions. This book walks you through the key elements of OpenCV and its powerful machine learning classes, while demonstrating how to get to grips with a range of models.

Master the intricacies of Apache Storm and develop real-time stream processing applications with ease About This Book ? Exploit the various real-time processing functionalities offered by Apache Storm such as parallelism, data partitioning, and more ? Integrate Storm with other Big Data technologies like Hadoop, HBase, and Apache Kafka ? An easy-to-understand guide to effortlessly create distributed applications with Storm Who This Book Is For If you are a Java developer who wants to enter into the world of real-time stream processing applications using Apache Storm, then this book is for you. No previous experience in Storm is required as this book starts from the basics. After finishing this book, you will be able to develop not-so-complex Storm applications. What You Will Learn ? Understand the core concepts of Apache Storm and real-time processing ? Follow the steps to deploy multiple nodes of Storm Cluster ? Create Trident topologies to support various message-processing semantics ? Make your cluster sharing effective using Storm scheduling ? Integrate Apache Storm with other Big Data technologies such as Hadoop, HBase, Kafka, and more ? Monitor the health of your Storm cluster In Detail Apache Storm is a real-time Big Data processing framework that processes large amounts of data reliably, guaranteeing that every message will be processed. Storm allows you to scale your data as it grows, making it an excellent platform to solve your big data problems. This extensive guide will help you understand right from the basics to the advanced topics of Storm. The book begins with a detailed introduction to real-time processing and where Storm fits in to solve these problems. You’ll get an understanding of deploying Storm on clusters by writing a basic Storm Hello World example. Next we’ll introduce you to Trident and you’ll get a clear understanding of how you can develop and deploy a trident topology. We cover topics such as monitoring, Storm Parallelism, scheduler and log processing, in a very easy to understand manner. You will also learn how to integrate Storm with other well-known Big Data technologies such as HBase, Redis, Kafka, and Hadoop to realize the full potential of Storm. With real-world examples and clear explanations, this book will ensure you will have a thorough mastery of Apache Storm. You will be able to use this knowledge to develop efficient, distributed real-time applications to cater to your business needs. Style and approach This easy-to-follow guide is full of examples and real-world applications to help you get an in-depth understanding of Apache Storm. This book covers the basics thoroughly and also delves into the intermediate and slightly advanced concepts of application development with Apache Storm.

Extract patterns and knowledge from your data in easy way using MATLAB About This Book ? Get your first steps into machine learning with the help of this easy-to-follow guide ? Learn regression, clustering, classification, predictive analytics, artificial neural networks and more with MATLAB ? Understand how your data works and identify hidden layers in the data with the power of machine learning. Who This Book Is For This book is for data analysts, data scientists, students, or anyone who is looking to get started with machine learning and want to build efficient data processing and predicting applications. A mathematical and statistical background will really help in following this book well. What You Will Learn ? Learn the introductory concepts of machine learning. ? Discover different ways to transform data using SAS XPORT, import and export tools, ? Explore the different types of regression techniques such as simple & multiple linear regression, ordinary least squares estimation, correlations and how to apply them to your data. ? Discover the basics of classification methods and how to implement Naive Bayes algorithm and Decision Trees in the Matlab environment. ? Uncover how to use clustering methods like hierarchical clustering to grouping data using the similarity measures. ? Know how to perform data fitting, pattern recognition, and clustering analysis with the help of MATLAB Neural Network Toolbox. ? Learn feature selection and extraction for dimensionality reduction leading to improved performance. In Detail MATLAB is the language of choice for many researchers and mathematics experts for machine learning. This book will help you build a foundation in machine learning using MATLAB for beginners. You’ll start by getting your system ready with t he MATLAB environment for machine learning and you’ll see how to easily interact with the Matlab workspace. We’ll then move on to data cleansing, mining and analyzing various data types in machine learning and you’ll see how to display data values on a plot. Next, you’ll get to know about the different types of regression techniques and how to apply them to your data using the MATLAB functions. You’ll understand the basic concepts of neural networks and perform data fitting, pattern recognition, and clustering analysis. Finally, you’ll explore feature selection and extraction techniques for dimensionality reduction for performance improvement. At the end of the book, you will learn to put it all together into real-world cases covering major machine learning algorithms and be comfortable in performing machine learning with MATLAB. Style and approach The book takes a very comprehensive approach to enhance your understanding of machine learning using MATLAB. Sufficient real-world examples and use cases are included in the book to help you grasp the concepts quickly and apply them easily in your day-to-day work.

Unlock the complexities of machine learning algorithms in Spark to generate useful data insights through this data analysis tutorial About This Book ? Process and analyze big data in a distributed and scalable way ? Write sophisticated Spark pipelines that incorporate elaborate extraction ? Build and use regression models to predict flight delays Who This Book Is For Are you a developer with a background in machine learning and statistics who is feeling limited by the current slow and “small data” machine learning tools? Then this is the book for you! In this book, you will create scalable machine learning applications to power a modern data-driven business using Spark. We assume that you already know the machine learning concepts and algorithms and have Spark up and running (whether on a cluster or locally) and have a basic knowledge of the various libraries contained in Spark. What You Will Learn ? Use Spark streams to cluster tweets online ? Run the PageRank algorithm to compute user influence ? Perform complex manipulation of DataFrames using Spark ? Define Spark pipelines to compose individual data transformations ? Utilize generated models for off-line/on-line prediction ? Transfer the learning from an ensemble to a simpler Neural Network ? Understand basic graph properties and important graph operations ? Use GraphFrames, an extension of DataFrames to graphs, to study graphs using an elegant query language ? Use K-means algorithm to cluster movie reviews dataset In Detail The purpose of machine learning is to build systems that learn from data. Being able to understand trends and patterns in complex data is critical to success; it is one of the key strategies to unlock growth in the challenging contemporary marketplace today. With the meteoric rise of machine learning, developers are now keen on finding out how can they make their Spark applications smarter. This book gives you access to transform data into actionable knowledge. The book commences by defining machine learning primitives by the MLlib and H2O libraries. You will learn how to use Binary classification to detect the Higgs Boson particle in the huge amount of data produced by CERN particle collider and classify daily health activities using ensemble Methods for Multi-Class Classification. Next, you will solve a typical regression problem involving flight delay predictions and write sophisticated Spark pipelines. You will analyze Twitter data with help of the doc2vec algorithm and K-means clustering. Finally, you will build different pattern mining models using MLlib, perform complex manipulation of DataFrames using Spark and Spark SQL, and deploy your app in a Spark streaming environment. Style and approach This book takes a practical approach to help you get to grips with using Spark for analytics and to implement machine learning algorithms. We'll teach you about advanced applications of machine learning through illustrative examples. These examples will equip you to harness the potential of machine learning, through Spark, in a variety of enterprise-grade systems.

Build consistent web apps with Redux by easily centralizing the state of your application. About This Book ? Write applications that behave consistently, run in different environments (client, server and native), and are easy to test ? Take your web apps to the next level by combining the power of Redux with other frameworks such as React and Angular ? Uncover the best practices and hidden features of Redux to build applications that are powerful, consistent, and maintainable Who This Book Is For This book targets developers who are already fluent in JavaScript but want to extend their web development skills to develop and maintain bigger applications. What You Will Learn ? Understand why and how Redux works ? Implement the basic elements of Redux ? Use Redux in combination with React/Angular to develop a web application ? Debug a Redux application ? Interface with external APIs with Redux ? Implement user authentication with Redux ? Write tests for all elements of a Redux application ? Implement simple and more advanced routing with Redux ? Learn about server-side rendering with Redux and React ? Create higher-order reducers for Redux ? Extend the Redux store via middleware In Detail The book starts with a short introduction to the principles and the ecosystem of Redux, then moves on to show how to implement the basic elements of Redux and put them together. Afterward, you are going to learn how to integrate Redux with other frameworks, such as React and Angular. Along the way, you are going to develop a blog application. To practice developing growing applications with Redux, we are going to start from nothing and keep adding features to our application throughout the book. You are going to learn how to integrate and use Redux DevTools to debug applications, and access external APIs with Redux. You are also going to get acquainted with writing tests for all elements of a Redux application. Furthermore, we are going to cover important concepts in web development, such as routing, user authentication, and communication with a backend server After explaining how to use Redux and how powerful its ecosystem can be, the book teaches you how to make your own abstractions on top of Redux, such as higher-order reducers and middleware. By the end of the book, you are going to be able to develop and maintain Redux applications with ease. In addition to learning about Redux, you are going be familiar with its ecosystem, and learn a lot about JavaScript itself, including best practices and patterns. Style and approach This practical guide will teach you how to develop a complex, data-intensive application leveraging the capabilities of the Redux framework.

Learn how to confidently install, configure, secure, and fully utilize your ArcGIS Enterprise system. About This Book ? Install and configure the components of ArcGIS Enterprise to meet your organization's requirements ? Administer all aspects of ArcGIS Enterprise through user interfaces and APIs ? Optimize and Secure ArcGIS Enterprise to make it run efficiently and effectively Who This Book Is For This book will be geared toward senior GIS analysts, GIS managers, GIS administrators, DBAs, GIS architects, and GIS engineers that need to install, configure, and administer ArcGIS Enterprise 10.5.1. What You Will Learn ? Effectively install and configure ArcGIS Enterprise, including the Enterprise geodatabase, ArcGIS Server, and Portal for ArcGIS ? Incorporate different methodologies to manage and publish services ? Utilize the security methods available in ArcGIS Enterprise ? Use Python and Python libraries from Esri to automate administrative tasks ? Identify the common pitfalls and errors to get your system back up and running quickly from an outage In Detail ArcGIS Enterprise, the next evolution of the ArcGIS Server product line, is a full-featured mapping and analytics platform. It includes a powerful GIS web services server and a dedicated Web GIS infrastructure for organizing and sharing your work. You will learn how to first install ArcGIS Enterprise to then plan, design, and finally publish and consume GIS services. You will install and configure an Enterprise geodatabase and learn how to administer ArcGIS Server, Portal, and Data Store through user interfaces, the REST API, and Python *s. This book starts off by explaining how ArcGIS Enterprise 10.5.1 is different from earlier versions of ArcGIS Server and covers the installation of all the components required for ArcGIS Enterprise. We then move on to geodatabase administration and content publication, where you will learn how to use ArcGIS Server Manager to view the server logs, stop and start services, publish services, define users and roles for security, and perform other administrative tasks. You will also learn how to apply security mechanisms on ArcGIS Enterprise and safely expose services to the public in a secure manner. Finally, you’ll use the RESTful administrator API to automate server management tasks using the Python *ing language. You’ll learn all the best practices and troubleshooting methods to streamline the management of all the interconnected parts of ArcGIS Enterprise. Style and approach The book takes a pragmatic approach, starting with installation & configuration of ArcGIS Enterprise to finally building a robust GIS web infrastructure for your organization.

Maximize your administration skills effectively and efficiently About This Book ? Implement cost-effective virtualization solutions for your organization with actionable recipes ? Explore the concepts of VMM with real-world use cases ? Use the latest features with VMM 2016 such as Cluster OS Rolling Upgrade, Guarded Fabric and Storage Spaces Direct Who This Book Is For If you are a solutions architect, technical consultant, administrator, or any other virtualization enthusiast who needs to use Microsoft System Center Virtual Machine Manager in a real-world environment, then this is the book for you. What You Will Learn ? Plan and design a VMM architecture for real-world deployment ? Configure fabric resources, including compute, networking, and storage ? Create and manage Storage Spaces Direct clusters in VMM ? Configure Guarded Fabric with Shielded VMs ? Create and deploy virtual machine templates and multi-tier services ? Manage Hyper-V and VMware environments from VMM ? Enhance monitoring and management capabilities ? Upgrade to VMM 2016 from previous versions In Detail Virtual Machine Manager (VMM) 2016 is part of the System Center suite to configure and manage datacenters and offers a unified management experience on-premises and Azure cloud. This book will be your best companion for day-to-day virtualization needs within your organization, as it takes you through a series of recipes to simplify and plan a highly scalable and available virtual infrastructure. You will learn the deployment tips, techniques, and solutions designed to show users how to improve VMM 2016 in a real-world scenario. The chapters are divided in a way that will allow you to implement the VMM 2016 and additional solutions required to effectively manage and monitor your fabrics and clouds. We will cover the most important new features in VMM 2016 across networking, storage, and compute, including brand new Guarded Fabric, Shielded VMs and Storage Spaces Direct. The recipes in the book provide step-by-step instructions giving you the simplest way to dive into VMM fabric concepts, private cloud, and integration with external solutions such as VMware, Operations Manager, and the Windows Azure Pack. By the end of this book, you will be armed with the knowledge you require to start designing and implementing virtual infrastructures in VMM 2016. Style and approach This book follows a recipe-based approach similar to our previous two successful editions, covering the practical application of the major features in VMM 2016.

Implement solutions by leveraging the power of the GO standard library and reducing dependency on external crates About This Book ? Develop high quality, fast and portable applications by leveraging the power of Go Standard Library. ? Practical recipes that will help you work with the standard library algorithms to boost your productivity as a Go developer. ? Compose your own algorithms without forfeiting the simplicity and elegance of the Standard Library. Who This Book Is For This book is for Go developers who would like to explore the power of Golang and learn how to use the Go standard library for various functionalities. The book assumes basic Go programming knowledge. What You Will Learn ? Access environmental variables ? Execute and work with child processes ? Manipulate strings by performing operations such as search, concatenate, and so on ? Parse and format the output of date/time information ? Operate on complex numbers and effective conversions between different number formats and bases ? Work with standard input and output ? Handle filesystem operations and file permissions ? Create TCP and HTTP servers, and access those servers with a client ? Utilize synchronization primitives ? Test your code In Detail Google's Golang will be the next talk of the town, with amazing features and a powerful library. This book will gear you up for using golang by taking you through recipes that will teach you how to leverage the standard library to implement a particular solution. This will enable Go developers to take advantage of using a rock-solid standard library instead of third-party frameworks. The book begins by exploring the functionalities available for interaction between the environment and the operating system. We will explore common string operations, date/time manipulations, and numerical problems. We'll then move on to working with the database, accessing the filesystem, and performing I/O operations. From a networking perspective, we will touch on client and server-side solutions. The basics of concurrency are also covered, before we wrap up with a few tips and tricks. By the end of the book, you will have a good overview of the features of the Golang standard library and what you can achieve with them. Ultimately, you will be proficient in implementing solutions with powerful standard libraries. Style and approach Solution based approach showcasing the power of Go standard library for easy practical implementations.

Learn to implement ASP.NET Core features to build effective software that can be scaled and maintained easily About This Book ? Practical solutions to recurring issues in the web development world ? Recipes on the latest features of ASP.Net Core 2.0 ? Coverage of Bootstrap, Angular, and JavaScript lets you supercharge your frontend Who This Book Is For This book is written for the ASP.NET developer who wants to deliver professional-standard software, quickly and efficiently. It's filled with hands-on recipes, practical advice, and guidance to help developers with every aspect of the ASP.NET development cycle. Whether you've just started out or are a seasoned pro, the Asp.Net Core 2.0 Cookbook is written for you. What You Will Learn ? Build ASP.Net Core 2.0 applications using HTTP services with WebApi ? Learn to unit-test, load test, and perform test applications using client-side and server-side frameworks ? Debug, monitor and troubleshoot ASP.Net Core 2.0 applications using popular tools ? Reuse components with NuGet and create modular components with middleware ? Create applications using client-side technologies such as HTML5, JavaScript, jQuery, and Angular ? Build responsive and dynamic UIs for your MVC apps using Bootstrap ? Leverage tools like Karma, Jasmine, QUnit, xUnit, Selenium, Microsoft Fakes, and Visual Studio 2017 Enterprise In Detail The ASP.NET Core 2.0 Framework has been designed to meet all the needs of today’s web developers. It provides better control, support for test-driven development, and cleaner code. Moreover, it’s lightweight and allows you to run apps on Windows, OSX and Linux, making it the most popular web framework with modern day developers. This book takes a unique approach to web development, using real-world examples to guide you through problems with ASP.NET Core 2.0 web applications. It covers Visual Studio 2017- and ASP.NET Core 2.0-specifc changes and provides general MVC development recipes. It explores setting up .NET Core, Visual Studio 2017, Node.js modules, and NuGet. Next, it shows you how to work with Inversion of Control data pattern and caching. We explore everyday ASP.NET Core MVC 2.0 patterns and go beyond it into troubleshooting. Finally, we lead you through migrating, hosting, and deploying your code. By the end of the book, you’ll not only have explored every aspect of ASP.NET Core MVC 2.0, you’ll also have a reference you can keep coming back to whenever you need to get the job done. Style and approach Asp.Net Core 2.0 has been redesigned to meet the needs of today's web developers. Open-source, cross-platform, and fully integrated with the most powerful front-end frameworks, it still has all the benefits of ease and speed of development that have made it one of the most popular web frameworks in production today. Asp.Net Core 2.0 Development Cookbook takes a unique approach to web development. Based around the tasks that you will be using every day when making websites, it will guide you through all the common problems you'll face when developing web applications.

Push the limits of what C - and you - can do, with this high-intensity guide to the most advanced capabilities of C Key Features * Make the most of C’s low-level control, flexibility, and high performance * A comprehensive guide to C’s most powerful and challenging features * A thought-provoking guide packed with hands-on exercises and examples Book Description There’s a lot more to C than knowing the language syntax. The industry looks for developers with a rigorous, scientific understanding of the principles and practices. Extreme C will teach you to use C’s advanced low-level power to write effective, efficient systems. This intensive, practical guide will help you become an expert C programmer. Building on your existing C knowledge, you will master preprocessor directives, macros, conditional compilation, pointers, and much more. You will gain new insight into algorithm design, functions, and structures. You will discover how C helps you squeeze maximum performance out of critical, resource-constrained applications. C still plays a critical role in 21st-century programming, remaining the core language for precision engineering, aviations, space research, and more. This book shows how C works with Unix, how to implement OO principles in C, and fully covers multi-processing. In Extreme C, Amini encourages you to think, question, apply, and experiment for yourself. The book is essential for anybody who wants to take their C to the next level. What you will learn * Build advanced C knowledge on strong foundations, rooted in first principles * Understand memory structures and compilation pipeline and how they work, and how to make most out of them * Apply object-oriented design principles to your procedural C code * Write low-level code that’s close to the hardware and squeezes maximum performance out of a computer system * Master concurrency, multithreading, multi-processing, and integration with other languages * Unit Testing and debugging, build systems, and inter-process communication for C programming Who this book is for Extreme C is for C programmers who want to dig deep into the language and its capabilities. It will help you make the most of the low-level control C gives you.

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.

Design, develop, and master efficient Power BI solutions for impactful business insights Key Features *Get to grips with the fundamentals of Microsoft Power BI *Combine data from multiple sources, create visuals, and publish reports across platforms *Understand Power BI concepts with real-world use cases Book Description Microsoft Power BI Complete Reference Guide gets you started with business intelligence by showing you how to install the Power BI toolset, design effective data models, and build basic dashboards and visualizations that make your data come to life. In this Learning Path, you will learn to create powerful interactive reports by visualizing your data and learn visualization styles, tips and tricks to bring your data to life. You will be able to administer your organization's Power BI environment to create and share dashboards. You will also be able to streamline deployment by implementing security and regular data refreshes. Next, you will delve deeper into the nuances of Power BI and handling projects. You will get acquainted with planning a Power BI project, development, and distribution of content, and deployment. You will learn to connect and extract data from various sources to create robust datasets, reports, and dashboards. Additionally, you will learn how to format reports and apply custom visuals, animation and analytics to further refine your data. By the end of this Learning Path, you will learn to implement the various Power BI tools such as on-premises gateway together along with staging and securely distributing content via apps. This Learning Path includes content from the following Packt products: *Microsoft Power BI Quick Start Guide by Devin Knight et al. *Mastering Microsoft Power BI by Brett Powell What you will learn *Connect to data sources using both import and DirectQuery options *Leverage built-in and custom visuals to design effective reports *Administer a Power BI cloud tenant for your organization *Deploy your Power BI Desktop files into the Power BI Report Server *Build efficient data retrieval and transformation processes Who this book is for Microsoft Power BI Complete Reference Guide is for those who want to learn and use the Power BI features to extract maximum information and make intelligent decisions that boost their business. If you have a basic understanding of BI concepts and want to learn how to apply them using Microsoft Power BI, then Learning Path is for you. It consists of real-world examples on Power BI and goes deep into the technical issues, covers additional protocols, and much more.

Conquer complex and interesting programming challenges by building robust and concurrent applications with caches, cryptography, and parallel programming. Key Features * Understand how to use .NET frameworks like the Task Parallel Library (TPL)and CryptoAPI * Develop a containerized application based on microservices architecture * Gain insights into memory management techniques in .NET Core Book Description This Learning Path shows you how to create high performing applications and solve programming challenges using a wide range of C# features. You’ll begin by learning how to identify the bottlenecks in writing programs, highlight common performance pitfalls, and apply strategies to detect and resolve these issues early. You'll also study the importance of micro-services architecture for building fast applications and implementing resiliency and security in .NET Core. Then, you'll study the importance of defining and testing boundaries, abstracting away third-party code, and working with different types of test double, such as spies, mocks, and fakes. In addition to describing programming trade-offs, this Learning Path will also help you build a useful toolkit of techniques, including value caching, statistical analysis, and geometric algorithms. This Learning Path includes content from the following Packt products: * C# 7 and .NET Core 2.0 High Performance by Ovais Mehboob Ahmed Khan * Practical Test-Driven Development using C# 7 by John Callaway, Clayton Hunt * The Modern C# Challenge by Rod Stephens What you will learn * Measure application performance using BenchmarkDotNet * Leverage the Task Parallel Library (TPL) and Parallel Language Integrated Query (PLINQ)library to perform asynchronous operations * Modify a legacy application to make it testable * Use LINQ and PLINQ to search directories for files matching patterns * Find areas of polygons using geometric operations * Randomize arrays and lists with extension methods * Use cryptographic techniques to encrypt and decrypt strings and files Who this book is for If you want to improve the speed of your code and optimize the performance of your applications, or are simply looking for a practical resource on test driven development, this is the ideal Learning Path for you. Some familiarity with C# and .NET will be beneficial.

Harness the power of Python objects and data structures to implement algorithms for analyzing your data and efficiently extracting information Key Features * Turn your designs into working software by learning the Python syntax * Write robust code with a solid understanding of Python data structures * Understand when to use the functional or the OOP approach Book Description This Learning Path helps you get comfortable with the world of Python. It starts with a thorough and practical introduction to Python. You’ll quickly start writing programs, building websites, and working with data by harnessing Python's renowned data science libraries. With the power of linked lists, binary searches, and sorting algorithms, you'll easily create complex data structures, such as graphs, stacks, and queues. After understanding cooperative inheritance, you'll expertly raise, handle, and manipulate exceptions. You will effortlessly integrate the object-oriented and not-so-object-oriented aspects of Python, and create maintainable applications using higher level design patterns. Once you’ve covered core topics, you’ll understand the joy of unit testing and just how easy it is to create unit tests. By the end of this Learning Path, you will have built components that are easy to understand, debug, and can be used across different applications. This Learning Path includes content from the following Packt products: * Learn Python Programming - Second Edition by Fabrizio Romano * Python Data Structures and Algorithms by Benjamin Baka * Python 3 Object-Oriented Programming by Dusty Phillips What you will learn * Use data structures and control flow to write code * Use functions to bundle together a sequence of instructions * Implement objects in Python by creating classes and defining methods * Design public interfaces using abstraction, encapsulation and information hiding * Raise, define, and manipulate exceptions using special error objects * Create bulletproof and reliable software by writing unit tests * Learn the common programming patterns and algorithms used in Python Who this book is for If you are relatively new to coding and want to write scripts or programs to accomplish tasks using Python, or if you are an object-oriented programmer for other languages and seeking a leg up in the world of Python, then this Learning Path is for you. Though not essential, it will help you to have basic knowledge of programming and OOP.

Create distributed applications with clever design patterns to solve complex problems Key Features * Set up and run distributed algorithms on a cluster using Dask and PySpark * Master skills to accurately implement concurrency in your code * Gain practical experience of Python design patterns with real-world examples Book Description This Learning Path shows you how to leverage the power of both native and third-party Python libraries for building robust and responsive applications. You will learn about profilers and reactive programming, concurrency and parallelism, as well as tools for making your apps quick and efficient. You will discover how to write code for parallel architectures using TensorFlow and Theano, and use a cluster of computers for large-scale computations using technologies such as Dask and PySpark. With the knowledge of how Python design patterns work, you will be able to clone objects, secure interfaces, dynamically choose algorithms, and accomplish much more in high performance computing. By the end of this Learning Path, you will have the skills and confidence to build engaging models that quickly offer efficient solutions to your problems. This Learning Path includes content from the following Packt products: * Python High Performance - Second Edition by Gabriele Lanaro * Mastering Concurrency in Python by Quan Nguyen * Mastering Python Design Patterns by Sakis Kasampalis What you will learn * Use NumPy and pandas to import and manipulate datasets * Achieve native performance with Cython and Numba * Write asynchronous code using asyncio and RxPy * Design highly scalable programs with application scaffolding * Explore abstract methods to maintain data consistency * Clone objects using the prototype pattern * Use the adapter pattern to make incompatible interfaces compatible * Employ the strategy pattern to dynamically choose an algorithm Who this book is for This Learning Path is specially designed for Python developers who want to build high-performance applications and learn about single core and multi-core programming, distributed concurrency, and Python design patterns. Some experience with Python programming language will help you get the most out of this Learning Path.

Delve into practical computer vision and image processing projects and get up to speed with advanced object detection techniques and machine learning algorithms Key Features * Discover best practices for engineering and maintaining OpenCV projects * Explore important deep learning tools for image classification * Understand basic image matrix formats and filters Book Description OpenCV is one of the best open source libraries available and can help you focus on constructing complete projects on image processing, motion detection, and image segmentation. This Learning Path is your guide to understanding OpenCV concepts and algorithms through real-world examples and activities. Through various projects, you'll also discover how to use complex computer vision and machine learning algorithms and face detection to extract the maximum amount of information from images and videos. In later chapters, you'll learn to enhance your videos and images with optical flow analysis and background subtraction. Sections in the Learning Path will help you get to grips with text segmentation and recognition, in addition to guiding you through the basics of the new and improved deep learning modules. By the end of this Learning Path, you will have mastered commonly used computer vision techniques to build OpenCV projects from scratch. This Learning Path includes content from the following Packt books: * Mastering OpenCV 4 - Third Edition by Roy Shilkrot and David Millán Escrivá * Learn OpenCV 4 By Building Projects - Second Edition by David Millán Escrivá, Vinícius G. Mendon?a, and Prateek Joshi What you will learn * Stay up-to-date with algorithmic design approaches for complex computer vision tasks * Work with OpenCV's most up-to-date API through various projects * Understand 3D scene reconstruction and Structure from Motion (SfM) * Study camera calibration and overlay augmented reality (AR) using the ArUco module * Create CMake scripts to compile your C++ application * Explore segmentation and feature extraction techniques * Remove backgrounds from static scenes to identify moving objects for surveillance * Work with new OpenCV functions to detect and recognize text with Tesseract Who this book is for If you are a software developer with a basic understanding of computer vision and image processing and want to develop interesting computer vision applications with OpenCV, this Learning Path is for you. Prior knowledge of C++ and familiarity with mathematical concepts will help you better understand the concepts in this Learning Path.