Build optimized applications in Kotlin by learning how to make use of the standard library features the smart way Key Features *Get the most out of the Kotlin library to develop high-quality portable applications *Explore the powerful support for data processing and I/O operations *Discover ways to enhance your Android application development Book Description Given the verbosity of Java, developers have turned to Kotlin for effective software development. The Kotlin standard library provides vital tools that make day-to-day Kotlin programming easier. This library features the core attributes of the language, such as algorithmic problems, design patterns, data processing, and working with files and data streams. The recipes in this book offer coding solutions that can be readily executed. The book covers various topics related to data processing, I/O operations, and collections transformation. We'll walk through effective design patterns in Kotlin and you'll understand how coroutines add new features to JavaScript. As you make your way through the chapters, you'll learn how to implement clean, reusable functions and scalable interfaces containing default implementations. In the concluding chapters, we'll provide recipes on functional programming concepts, such as lambdas, monads, functors, and Kotlin scoping functions. By the end of the book, you'll be able to address a range of problems that Kotlin developers face by implementing easy-to-follow solutions. What you will learn *Work with ranges, progressions, and sequences in use cases *Add new functionalities to current classes with Kotlin extensions *Understand elements such as lambdas, closures, and monads *Build a REST API consumer with Retrofit and a coroutine adapter *Discover useful tips and solutions for making your Android projects *Explore the benefits of standard library features Who this book is for This book is for software developers who are familiar with Kotlin’s basics and want to discover more advanced features and concepts, especially those provided by the Kotlin standard library. It’s also ideal for experienced software developers who are familiar with the functional programming paradigm and other programming languages who want to switch to Kotlin. It will also help Java developers switch to Kotlin and integrate it into existing Java Virtual Machine (JVM) projects.

Make web applications run faster by using advanced PHP, SQL and JavaScript techniques About This Book ? Use a customized PHP stack to create efficient data-driven web applications ? Ensure seamless implementation of a JavaScript & HTML 5 CSS based frontend and PHP based backend. ? Learn about problem identification, best strategies, and UI design patterns as well to build a clean, fast web application Who This Book Is For The audience for this book would be PHP developers who have some basic knowledge of PHP programming and Web technologies. JavaScript programming knowledge is not necessary. What You Will Learn ? Install, confgure, and use profling and benchmarking testing tools ? Understand how to recognize optimizable data structures and functions to effectively optimize a PHP7 application ? Diagnose bad SQL query performance and discover ways to optimize it ? Grasp modern SQL techniques to optimize complex SQL queries ? Identify and simplify overly complex JavaScript code ? Explore and implement UI design principles that effectively enhance the performance ? Combine web technologies to boost web server performance In Detail This book will get you started with the latest benchmarking, profiling and monitoring tools for PHP, MySQL and JavaScript using Docker-based technologies. From optimizing PHP 7 code to learning asynchronous programming, from implementing Modern SQL solutions to discovering Functional JavaScript techniques, this book covers all the latest developments in Faster Web technologies. You will not only learn to determine the best optimization strategies, but also how to implement them. Along the way, you will learn how to profile your PHP scripts with Blackfire.io, monitor your Web applications, measure database performance, optimize SQL queries, explore Functional JavaScript, boost Web server performance in general and optimize applications when there is nothing left to optimize by going beyond performance. After reading this book, you will know how to boost the performance of any Web application and make it part of what has come to be known as the Faster Web. Style and approach The book has a step by step practical approach to developing highly efficient Web applications, with many practical and useful code snippets.

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Introducing modular techniques for building sophisticated programs using PythonAbout This Book·The book would help you develop succinct, expressive programs using modular deign·The book would explain best practices and common idioms through carefully explained and structured examples·It will have broad appeal as far as target audience is concerned and there would be take away for all beginners to PythonWho This Book Is ForThis book is intended for beginner to intermediate level Python programmers who wish to learn how to use modules and packages within their programs. While readers must understand the basics of Python programming, no knowledge of modular programming techniques is required.What You Will Learn·Learn how to use modules and packages to organize your Python code·Understand how to use the import statement to load modules and packages into your program·Use common module patterns such as abstraction and encapsulation to write better programs·Discover how to create self-testing Python packages·Create reusable modules that other programmers can use·Learn how to use GitHub and the Python Package Index to share your code with other people·Make use of modules and packages that others have written·Use modular techniques to build robust systems that can handle complexity and changing requirements over timeIn DetailPython has evolved over the years and has become the primary choice of developers in various fields. The purpose of this book is to help readers develop readable, reliable, and maintainable programs in Python.Starting with an introduction to the concept of modules and packages, this book shows how you can use these building blocks to organize a complex program into logical parts and make sure those parts are working correctly together.Using clearly written, real-world examples, this book demonstrates how you can use modular techniques to build better programs. A number of common modular programming patterns are covered, including divide-and-conquer, abstraction, encapsulation, wrappers and extensibility. You will also learn how to test your modules and packages, how to prepare your code for sharing with other people, and how to publish your modules and packages on GitHub and the Python Package Index so that other people can use them. Finally, you will learn how to use modular design techniques to be a more effective programmer.Style and approachThis book will be simple and straightforward, focusing on imparting learning through a wide array of examples that the readers can put into use as they read through the book. They should not only be able to understand the way modules help in improving development, but they should also be able to improvise on their techniques of writing concise and effective code.

Start building fast and robust applications with the power of Rust by your sideAbout This Book·Get started with the language to build scalable and high performance applications·This book will help C#/C++ developers gain better performance and memory management·Discover the power of Rust when developing concurrent applications for large and scalable softwareWho This Book Is ForThe book is for absolute beginners to Rust, who want to build high performance, concurrent applications for their projects. It is suitable for developers who have a basic knowledge of programming and developers who are using the C#/C++ language to write their applications. No knowledge of Rust is expected.What You Will Learn·Set up Rust for Windows, Linux, and OS X·Write effective code using Rust·Expand your Rust applications using libraries·Interface existing non-Rust libraries with your Rust applications·Use the standard library within your applications·Understand memory management within Rust and speed efficiency when passing variables·Create more complex data types·Study concurrency in Rust with multi-threaded applications and sync threading techniques to improve the performance of an application problemIn DetailRust is a highly concurrent and high performance language that focuses on safety and speed, memory management, and writing clean code. It also guarantees thread safety, and its aim is to improve the performance of existing applications. Its potential is shown by the fact that it has been backed by Mozilla to solve the critical problem of concurrency.Learning Rust will teach you to build concurrent, fast, and robust applications. From learning the basic syntax to writing complex functions, this book will is your one stop guide to get up to speed with the fundamentals of Rust programming. We will cover the essentials of the language, including variables, procedures, output, compiling, installing, and memory handling.You will learn how to write object-oriented code, work with generics, conduct pattern matching, and build macros. You will get to know how to communicate with users and other services, as well as getting to grips with generics, scoping, and more advanced conditions. You will also discover how to extend the compilation unit in Rust.By the end of this book, you will be able to create a complex application in Rust to move forward with.Style and approachThis comprehensive book will focus on the Rust syntax, functions, data types, and conducting pattern matching for programmers. It is divided into three parts and each part of the book has an objective to enable the readers to create their own applications at an appropriate level, ultimately towards creating complex applications.

Learn to build powerful and scalable applications with Flux, the architecture that serves billions of Facebook users every dayAbout This Book·This the first resource dedicated to the new architectural pattern that powers Facebook·You'll learn all the tips and tricks you need to get the most out of Flux·Filled with practical, hands-on samples, you'll not only understand how Flux works, but will be able to start building Flux-powered applications straight away·Written by Adam Boduch, software architect at Virtustream (EMC), and author of JavaScript at Scale, JavaScript Concurrency, and jQuery UI Cookbook for Packt PublishingWho This Book Is ForAre you trying to use React, but are struggling to get your head around Flux? Maybe you're tired of MV* spaghetti code at scale? Do you find yourself asking what the Flux?!Flux Architecture will guide you through everything you need to understand the Flux pattern, and design and build powerful web applications that rely on the Flux architecture.You don't need to know what Flux is or how it works to read along with the book. No knowledge of Flux's partner technology, ReactJS, is necessary to follow along, but it is recommended that you have a good working knowledge of JavaScript.What You Will Learn·Understand the Flux pattern and how it will impact your React applications·Build real-world applications that rely on Flux·Handle asynchronous actions in your application·Implement immutable stores with Immutable.js·Replace React.js with alternate View components such as jQuery and Handlebars·Test and benchmark your Flux architecture using Jest—Facebook's enhancement of the Jasmine libraryIn DetailWhilst React has become Facebook's poster-child for clean, complex, and modern web development, it has quietly been underpinned by its simplicity. It's just a view. The real beauty in React is actually the architectural pattern that handles data in and out of React applications: Flux. With Flux, you're able to build data-rich applications that engage your users, and scale to meet every demand. It is a key part of the Facebook technology stack that serves billions of users every day.This book will start by introducing the Flux pattern and help you get an understanding of what it is and how it works. After this, we'll build real-world React applications that highlight the power and simplicity of Flux in action. Finally, we look at the landscape of Flux and explore the Alt and Redux libraries that make React and Flux developments easier.Filled with fully-worked examples and code-first explanations, by the end of the book, you'll not only have a rock solid understanding of the architecture, but will be ready to implement Flux architecture in anger.Style and approachThis book is filled with practical, hands-on examples. You'll not only understand how Flux works, but will be able to start building Flux-powered applications straight away.

Design and implement efficient RESTful solutions with this practical hands-on guideAbout This Book·Create a fully featured RESTful API solution from scratch.·Learn how to leverage Node.JS, Express, MongoDB and NoSQL datastores to give an extra edge to your REST API design.·Use this practical guide to integrate MongoDB in your Node.js application.Who This Book Is ForThe ideal target audience for this book is web developers who have some experience with RESTful services. Familiarity with basic JavaScript programming techniques is required. No prior experience with Node.JS or Express.js is required.What You Will Learn·Install, develop, and test your own Node.js user modules·Comprehend the differences between an HTTP and a RESTful application·Optimize RESTful service URI routing with best practices·Eliminate third-party dependencies in your tests with mocking·Learn about NoSQL data stores and integrate MongoDB in your Node.js application with Mongoose·Secure your services with NoSQL database integration within Node.js applications·Enrich your development skills to create scalable, server-side, RESTful applications based on the Node.js platformIn DetailIn this era of cloud computing, every data provisioning solution is built in a scalable and fail-safe way. Thus, when building RESTful services, the right choice for the underlying platform is vital. Node.js, with its asynchronous, event-driven architecture, is exactly the right choice to build RESTful APIs.This book will help you enrich your development skills to create scalable, server-side, RESTful applications based on the Node.js platform.Starting with the fundamentals of REST, you will understand why RESTful web services are better data provisioning solution than other technologies. You will start setting up a development environment by installing Node.js, Express.js, and other modules. Next, you will write a simple HTTP request handler and create and test Node.js modules using automated tests and mock objects. You will then have to choose the most appropriate data storage type, having options between a key/value or document data store, and also you will implement automated tests for it. This module will evolve chapter by chapter until it turns into a full-fledged and secure Restful service.Style and approachCreate state of the art RESTful API solutions leveraging Node.JS 4.x.

A practical guide to rapidly and efficiently mastering Docker containers, along with tips and tricks learned in the field.About This Book·Use Docker containers, horizontal node scaling, modern orchestration tools (Docker Swarm, Kubernetes, and Mesos) and Continuous Integration/Continuous Delivery to manage your infrastructure.·Increase service density by turning often-idle machines into hosts for numerous Docker services.·Learn what it takes to build a true container infrastructure that is scalable, reliable, and resilient in the face of increased complexities from using container infrastructures.·Find out how to identify, debug, and mitigate most real-world, undocumented issues when deploying your own Docker infrastructure.·Learn tips and tricks of the trade from existing Docker infrastructures running in production environments.Who This Book Is ForThis book is aimed at system administrators, developers, DevOps engineers, and software engineers who want to get concrete, hands-on experience deploying multi-tier web applications and containerized microservices using Docker. This book is also for anyone who has worked on deploying services in some fashion and wants to take their small-scale setups to the next level (or simply to learn more about the process).What You Will Learn·Set up a working development environment and create a simple web service to demonstrate the basics·Learn how to make your service more usable by adding a database and an app server to process logic·Add resilience to your services by learning how to horizontally scale with a few containers on a single node·Master layering isolation and messaging to simplify and harden the connectivity between containers·Learn about numerous issues encountered at scale and their workarounds, from the kernel up to code versioning·Automate the most important parts of your infrastructure with continuous integrationIn DetailDeploying Docker into production is considered to be one of the major pain points in developing large-scale infrastructures, and the documentation available online leaves a lot to be desired. With this book, you will learn everything you wanted to know to effectively scale your deployments globally and build a resilient, scalable, and containerized cloud platform for your own use.The book starts by introducing you to the containerization ecosystem with some concrete and easy-to-digest examples; after that, you will delve into examples of launching multiple instances of the same container. From there, you will cover orchestration, multi-node setups, volumes, and almost every relevant component of this new approach to deploying services. Using intertwined approaches, the book will cover battle-tested tooling, or issues likely to be encountered in real-world scenarios, in detail. You will also learn about the other supporting components required for a true PaaS deployment and discover common options to tie the whole infrastructure together.At the end of the book, you learn to build a small, but functional, PaaS (to appreciate the power of the containerized service approach) and continue to explore real-world approaches to implementing even larger global-scale services.Style and approachThis in-depth learning guide shows you how to deploy your applications in production using Docker (from the basic steps to advanced concepts) and how to overcome challenges in Docker-based infrastructures. The book also covers practical use-cases in real-world examples, and provides tips and tricks on the various topics.

Discover various techniques to develop maintainable code and keep it in shape. Key Features * Learn all about refactoring - why it is important and how to do it * Discover easy ways to refactor code with examples * Explore techniques that can be applied to most other programming languages Book Description Refactoring improves your code without changing its behavior. With refactoring, the best approach is to apply small targeted changes to a codebase. Instead of doing a huge sweeping change to your code, refactoring is better as a long-term and continuous enterprise. Refactoring TypeScript explains how to spot bugs and remove them from your code. You’ll start by seeing how wordy conditionals, methods, and null checks make code unhealthy and unstable. Whether it is identifying messy nested conditionals or removing unnecessary methods, this book will show various techniques to avoid these pitfalls and write code that is easier to understand, maintain, and test. By the end of the book, you’ll have learned some of the main causes of unhealthy code, tips to identify them and techniques to address them. What you will learn * Spot and fix common code smells to create code that is easier to read and understand * Discover ways to identify long methods and refactor them * Create objects that keep your code flexible, maintainable, and testable * Apply the Single Responsibility Principle to develop less-coupled code * Discover how to combine different refactoring techniques * Learn ways to solve the issues caused by overusing primitives Who this book is for This book is designed for programmers who are looking to explore various refactoring techniques to develop healthy and maintainable code. Some experience in JavaScript and TypeScript can help you easily grasp the concepts explained in this book.

Learn a modern approach to data analysis using Python to harness the power of programming and AI across your data. Detailed case studies bring this modern approach to life across visual data, social media, graph algorithms, and time series analysis. Key Features *Bridge your data analysis with the power of programming, complex algorithms, and AI *Use Python and its extensive libraries to power your way to new levels of data insight *Work with AI algorithms, TensorFlow, graph algorithms, NLP, and financial time series *Explore this modern approach across with key industry case studies and hands-on projects Book Description Data Analysis with Python offers a modern approach to data analysis so that you can work with the latest and most powerful Python tools, AI techniques, and open source libraries. Industry expert David Taieb shows you how to bridge data science with the power of programming and algorithms in Python. You'll be working with complex algorithms, and cutting-edge AI in your data analysis. Learn how to analyze data with hands-on examples using Python-based tools and Jupyter Notebook. You'll find the right balance of theory and practice, with extensive code files that you can integrate right into your own data projects. Explore the power of this approach to data analysis by then working with it across key industry case studies. Four fascinating and full projects connect you to the most critical data analysis challenges you’re likely to meet in today. The first of these is an image recognition application with TensorFlow – embracing the importance today of AI in your data analysis. The second industry project analyses social media trends, exploring big data issues and AI approaches to natural language processing. The third case study is a financial portfolio analysis application that engages you with time series analysis - pivotal to many data science applications today. The fourth industry use case dives you into graph algorithms and the power of programming in modern data science. You'll wrap up with a thoughtful look at the future of data science and how it will harness the power of algorithms and artificial intelligence. What you will learn *A new toolset that has been carefully crafted to meet for your data analysis challenges *Full and detailed case studies of the toolset across several of today’s key industry contexts *Become super productive with a new toolset across Python and Jupyter Notebook *Look into the future of data science and which directions to develop your skills next Who this book is for This book is for developers wanting to bridge the gap between them and data scientists. Introducing PixieDust from its creator, the book is a great desk companion for the accomplished Data Scientist. Some fluency in data interpretation and visualization is assumed. It will be helpful to have some knowledge of Python, using Python libraries, and some proficiency in web development.

Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and Keras Key Features *Implement machine learning algorithms to build, train, and validate algorithmic models *Create your own algorithmic design process to apply probabilistic machine learning approaches to trading decisions *Develop neural networks for algorithmic trading to perform time series forecasting and smart analytics Book Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This book enables you to use a broad range of supervised and unsupervised algorithms to extract signals from a wide variety of data sources and create powerful investment strategies. This book shows how to access market, fundamental, and alternative data via API or web scraping and offers a framework to evaluate alternative data. You’ll practice the ML work?ow from model design, loss metric definition, and parameter tuning to performance evaluation in a time series context. You will understand ML algorithms such as Bayesian and ensemble methods and manifold learning, and will know how to train and tune these models using pandas, statsmodels, sklearn, PyMC3, xgboost, lightgbm, and catboost. This book also teaches you how to extract features from text data using spaCy, classify news and assign sentiment scores, and to use gensim to model topics and learn word embeddings from financial reports. You will also build and evaluate neural networks, including RNNs and CNNs, using Keras and PyTorch to exploit unstructured data for sophisticated strategies. Finally, you will apply transfer learning to satellite images to predict economic activity and use reinforcement learning to build agents that learn to trade in the OpenAI Gym. What you will learn *Implement machine learning techniques to solve investment and trading problems *Leverage market, fundamental, and alternative data to research alpha factors *Design and fine-tune supervised, unsupervised, and reinforcement learning models *Optimize portfolio risk and performance using pandas, NumPy, and scikit-learn *Integrate machine learning models into a live trading strategy on Quantopian *Evaluate strategies using reliable backtesting methodologies for time series *Design and evaluate deep neural networks using Keras, PyTorch, and TensorFlow *Work with reinforcement learning for trading strategies in the OpenAI Gym Who this book is for Hands-On Machine Learning for Algorithmic Trading is for data analysts, data scientists, and Python developers, as well as investment analysts and portfolio managers working within the finance and investment industry. If you want to perform efficient algorithmic trading by developing smart investigating strategies using machine learning algorithms, this is the book for you. Some understanding of Python and machine learning techniques is mandatory.

Explore a diverse set of meta-learning algorithms and techniques to enable human-like cognition for your machine learning models using various Python frameworks Key Features *Understand the foundations of meta learning algorithms *Explore practical examples to explore various one-shot learning algorithms with its applications in TensorFlow *Master state of the art meta learning algorithms like MAML, reptile, meta SGD Book Description Meta learning is an exciting research trend in machine learning, which enables a model to understand the learning process. Unlike other ML paradigms, with meta learning you can learn from small datasets faster. Hands-On Meta Learning with Python starts by explaining the fundamentals of meta learning and helps you understand the concept of learning to learn. You will delve into various one-shot learning algorithms, like siamese, prototypical, relation and memory-augmented networks by implementing them in TensorFlow and Keras. As you make your way through the book, you will dive into state-of-the-art meta learning algorithms such as MAML, Reptile, and CAML. You will then explore how to learn quickly with Meta-SGD and discover how you can perform unsupervised learning using meta learning with CACTUs. In the concluding chapters, you will work through recent trends in meta learning such as adversarial meta learning, task agnostic meta learning, and meta imitation learning. By the end of this book, you will be familiar with state-of-the-art meta learning algorithms and able to enable human-like cognition for your machine learning models. What you will learn *Understand the basics of meta learning methods, algorithms, and types *Build voice and face recognition models using a siamese network *Learn the prototypical network along with its variants *Build relation networks and matching networks from scratch *Implement MAML and Reptile algorithms from scratch in Python *Work through imitation learning and adversarial meta learning *Explore task agnostic meta learning and deep meta learning Who this book is for Hands-On Meta Learning with Python is for machine learning enthusiasts, AI researchers, and data scientists who want to explore meta learning as an advanced approach for training machine learning models. Working knowledge of machine learning concepts and Python programming is necessary.

Create a real-world application in Go and explore various frameworks and methodologies for full-stack development Key Features * Organize your isomorphic codebase to enhance the maintainability of your application * Build web APIs and middleware in the Go language by making use of the popular Gin framework * Implement real-time web application functionality with WebSockets Book Description The Go programming language has been rapidly adopted by developers for building web applications. With its impressive performance and ease of development, Go enjoys the support of a wide variety of open source frameworks, for building scalable and high-performant web services and apps. Hands-On Full Stack Development with Go is a comprehensive guide that covers all aspects of full stack development with Go. This clearly written, example-rich book begins with a practical exposure to Go development and moves on to build a frontend with the popular React framework. From there, you will build RESTful web APIs utilizing the Gin framework. After that, we will dive deeper into important software backend concepts, such as connecting to the database via an ORM, designing routes for your services, securing your services, and even charging credit cards via the popular Stripe API. We will also cover how to test, and benchmark your applications efficiently in a production environment. In the concluding chapters, we will cover isomorphic developments in pure Go by learning about GopherJS. As you progress through the book, you'll gradually build a musical instrument online store application from scratch. By the end of the book, you will be confident in taking on full stack web applications in Go. What you will learn * Understand Go programming by building a real-world application * Learn the React framework to develop a frontend for your application * Understand isomorphic web development utilizing the GopherJS framework * Explore methods to write RESTful web APIs in Go using the Gin framework * Learn practical topics such as ORM layers, secure communications, and Stripe's API * Learn methods to benchmark and test web APIs in Go Who this book is for Hands-On Full Stack Development with Go will appeal to developers who are looking to start building amazing full stack web applications in Go. Basic knowhow of Go language and JavaScript is expected. The book targets web developers who are looking to move to the Go language.

Learn how to build complete machine learning systems with IBM Cloud and Watson Machine learning services Key Features * Implement data science and machine learning techniques to draw insights from real-world data * Understand what IBM Cloud platform can help you to implement cognitive insights within applications * Understand the role of data representation and feature extraction in any machine learning system Book Description IBM Cloud is a collection of cloud computing services for data analytics using machine learning and artificial intelligence (AI). This book is a complete guide to help you become well versed with machine learning on the IBM Cloud using Python. Hands-On Machine Learning with IBM Watson starts with supervised and unsupervised machine learning concepts, in addition to providing you with an overview of IBM Cloud and Watson Machine Learning. You'll gain insights into running various techniques, such as K-means clustering, K-nearest neighbor (KNN), and time series prediction in IBM Cloud with real-world examples. The book will then help you delve into creating a Spark pipeline in Watson Studio. You will also be guided through deep learning and neural network principles on the IBM Cloud using TensorFlow. With the help of NLP techniques, you can then brush up on building a chatbot. In later chapters, you will cover three powerful case studies, including the facial expression classification platform, the automated classification of lithofacies, and the multi-biometric identity authentication platform, helping you to become well versed with these methodologies. By the end of this book, you will be ready to build efficient machine learning solutions on the IBM Cloud and draw insights from the data at hand using real-world examples. What you will learn * Understand key characteristics of IBM machine learning services * Run supervised and unsupervised techniques in the cloud * Understand how to create a Spark pipeline in Watson Studio * Implement deep learning and neural networks on the IBM Cloud with TensorFlow * Create a complete, cloud-based facial expression classification solution * Use biometric traits to build a cloud-based human identification system Who this book is for This beginner-level book is for data scientists and machine learning engineers who want to get started with IBM Cloud and its machine learning services using practical examples. Basic knowledge of Python and some understanding of machine learning will be useful.

A practical guide to getting the most out of Excel, using it for data preparation, applying machine learning models (including cloud services) and understanding the outcome of the data analysis. Key Features * Use Microsoft's product Excel to build advanced forecasting models using varied examples * Cover range of machine learning tasks such as data mining, data analytics, smart visualization, and more * Derive data-driven techniques using Excel plugins and APIs without much code required Book Description We have made huge progress in teaching computers to perform difficult tasks, especially those that are repetitive and time-consuming for humans. Excel users, of all levels, can feel left behind by this innovation wave. The truth is that a large amount of the work needed to develop and use a machine learning model can be done in Excel. The book starts by giving a general introduction to machine learning, making every concept clear and understandable. Then, it shows every step of a machine learning project, from data collection, reading from different data sources, developing models, and visualizing the results using Excel features and offerings. In every chapter, there are several examples and hands-on exercises that will show the reader how to combine Excel functions, add-ins, and connections to databases and to cloud services to reach the desired goal: building a full data analysis flow. Different machine learning models are shown, tailored to the type of data to be analyzed. At the end of the book, the reader is presented with some advanced use cases using Automated Machine Learning, and artificial neural network, which simplifies the analysis task and represents the future of machine learning. What you will learn * Use Excel to preview and cleanse datasets * Understand correlations between variables and optimize the input to machine learning models * Use and evaluate different machine learning models from Excel * Understand the use of different visualizations * Learn the basic concepts and calculations to understand how artificial neural networks work * Learn how to connect Excel to the Microsoft Azure cloud * Get beyond proof of concepts and build fully functional data analysis flows Who this book is for This book is for data analysis, machine learning enthusiasts, project managers, and someone who doesn't want to code much for performing core tasks of machine learning. Each example will help you perform end-to-end smart analytics. Working knowledge of Excel is required.

Use Ansible to configure your systems, deploy software, and orchestrate advanced IT tasks Key Features * Get familiar with the fundamentals of Ansible 2.7 * Understand how to use Ansible Tower to scale your IT automation * Gain insights into how to develop and test Ansible playbooks Book Description Ansible is an open source automation platform that assists organizations with tasks such as application deployment, orchestration, and task automation. With the release of Ansible 2.7, even complex tasks can be handled much more easily than before. Learning Ansible 2.7 will help you take your first steps toward understanding the fundamentals and practical aspects of Ansible by introducing you to topics such as playbooks, modules, and the installation of Linux, Berkeley Software Distribution (BSD), and Windows support. In addition to this, you will focus on various testing strategies, deployment, and orchestration to build on your knowledge. The book will then help you get accustomed to features including cleaner architecture, task blocks, and playbook parsing, which can help you to streamline automation processes. Next, you will learn how to integrate Ansible with cloud platforms such as Amazon Web Services (AWS) before gaining insights into the enterprise versions of Ansible, Ansible Tower and Ansible Galaxy. This will help you to use Ansible to interact with different operating systems and improve your working efficiency. By the end of this book, you will be equipped with the Ansible skills you need to automate complex tasks for your organization. What you will learn * Create a web server using Ansible * Write a custom module and test it * Deploy playbooks in the production environment * Troubleshoot networks using Ansible * Use Ansible Galaxy and Ansible Tower during deployment * Deploy an application with Ansible on AWS, Azure and DigitalOcean Who this book is for This beginner-level book is for system administrators who want to automate their organization's infrastructure using Ansible 2.7. No prior knowledge of Ansible is required

Create advanced applications with Python and OpenCV, exploring the potential of facial recognition, machine learning, deep learning, web computing and augmented reality. Key Features * Develop your computer vision skills by mastering algorithms in Open Source Computer Vision 4 (OpenCV 4)and Python * Apply machine learning and deep learning techniques with TensorFlow, Keras, and PyTorch * Discover the modern design patterns you should avoid when developing efficient computer vision applications Book Description OpenCV is considered to be one of the best open source computer vision and machine learning software libraries. It helps developers build complete projects in relation to image processing, motion detection, or image segmentation, among many others. OpenCV for Python enables you to run computer vision algorithms smoothly in real time, combining the best of the OpenCV C++ API and the Python language. In this book, you'll get started by setting up OpenCV and delving into the key concepts of computer vision. You'll then proceed to study more advanced concepts and discover the full potential of OpenCV. The book will also introduce you to the creation of advanced applications using Python and OpenCV, enabling you to develop applications that include facial recognition, target tracking, or augmented reality. Next, you'll learn machine learning techniques and concepts, understand how to apply them in real-world examples, and also explore their benefits, including real-time data production and faster data processing. You'll also discover how to translate the functionality provided by OpenCV into optimized application code projects using Python bindings. Toward the concluding chapters, you'll explore the application of artificial intelligence and deep learning techniques using the popular Python libraries TensorFlow, and Keras. By the end of this book, you'll be able to develop advanced computer vision applications to meet your customers' demands. What you will learn * Handle files and images, and explore various image processing techniques * Explore image transformations, including translation, resizing, and cropping * Gain insights into building histograms * Brush up on contour detection, filtering, and drawing * Work with Augmented Reality to build marker-based and markerless applications * Work with the main machine learning algorithms in OpenCV * Explore the deep learning Python libraries and OpenCV deep learning capabilities * Create computer vision and deep learning web applications Who this book is for This book is designed for computer vision developers, engineers, and researchers who want to develop modern computer vision applications. Basic experience of OpenCV and Python programming is a must.

Write efficient, reusable scripts to build custom characters, game environments, and control enemy AI Key Features * Build captivating multiplayer games using Unreal Engine and C++ * Incorporate existing C++ libraries into your game to add extra functionality such as hardware integration * Practical solutions for memory management, error handling, inputs, and collision for your game codebase Book Description Unreal Engine 4 (UE4) is a popular and award-winning game engine that powers some of the most popular games. A truly powerful tool for game development, there has never been a better time to use it for both commercial and independent projects. With more than 100 recipes, this book shows how to unleash the power of C++ while developing games with Unreal Engine. This book takes you on a journey to jumpstart your C++ and UE4 development skills. You will start off by setting up UE4 for C++ development and learn how to work with Visual Studio, a popular code editor. You will learn how to create C++ classes and structs the Unreal way. This will be followed by exploring memory management, smart pointers, and debugging your code. You will then learn how to make your own Actors and Components through code and how to handle input and collision events. You will also get exposure to many elements of game development including creating user interfaces, artificial intelligence, and writing code with networked play in mind. You will also learn how to add on to the Unreal Editor itself. With a range of task-oriented recipes, this book provides actionable information about writing code for games with UE4 using C++. By the end of the book, you will be empowered to become a top-notch developer with UE4 using C++ as your scripting language! What you will learn * Create C++ classes and structs that integrate well with UE4 and the Blueprints editor * Discover how to work with various APIs that Unreal Engine already contains * Utilize advanced concepts such as events, delegates, and interfaces in your UE4 projects * Build user interfaces using Canvas and UMG through C++ * Extend the Unreal Editor by creating custom windows and editors * Implement AI tasks and services using C++, Blackboard, and Behavior Trees * Write C++ code with networking in mind and replicate properties and functions Who this book is for If you are really passionate game developer looking for solutions to common scripting problems, then this is the book for you. Understanding of the fundamentals of game design and C++ is expected to get the most from this book.