Build clever, collaborative, and powerful automation systems with the Raspberry Pi and Python. Key Features * Create your own Pi-Rover or Pi-Hexipod robots * Develop practical applications in Python using Raspberry Pi * Build your own Jarvis, a highly advanced computerized AI Book Description This Learning Path takes you on a journey in the world of robotics and teaches you all that you can achieve with Raspberry Pi and Python. It teaches you to harness the power of Python with the Raspberry Pi 3 and the Raspberry Pi zero to build superlative automation systems that can transform your business. You will learn to create text classifiers, predict sentiment in words, and develop applications with the Tkinter library. Things will get more interesting when you build a human face detection and recognition system and a home automation system in Python, where different appliances are controlled using the Raspberry Pi. With such diverse robotics projects, you'll grasp the basics of robotics and its functions, and understand the integration of robotics with the IoT environment. By the end of this Learning Path, you will have covered everything from configuring a robotic controller, to creating a self-driven robotic vehicle using Python. * Raspberry Pi 3 Cookbook for Python Programmers - Third Edition by Tim Cox, Dr. Steven Lawrence Fernandes * Python Programming with Raspberry Pi by Sai Yamanoor, Srihari Yamanoor * Python Robotics Projects by Prof. Diwakar Vaish What you will learn * Build text classifiers and predict sentiment in words with the Tkinter library * Develop human face detection and recognition systems * Create a neural network module for optical character recognition * Build a mobile robot using the Raspberry Pi as a controller * Understand how to interface sensors, actuators, and LED displays work * Apply machine learning techniques to your models * Interface your robots with Bluetooth Who this book is for This Learning Path is specially designed for Python developers who want to take their skills to the next level by creating robots that can enhance people’s lives. Familiarity with Python and electronics will aid understanding the concepts in this Learning Path.

Get up to speed with creational, structural, behavioral and concurrent patterns in Delphi to write clear, concise and effective code Key Features * Delve into the core patterns and components of Delphi in order to master your application's design * Brush up on tricks, techniques, and best practices to solve common design and architectural challenges * Choose the right patterns to improve your program’s efficiency and productivity Book Description Design patterns have proven to be the go-to solution for many common programming scenarios. This book focuses on design patterns applied to the Delphi language. The book will provide you with insights into the language and its capabilities of a runtime library. You'll start by exploring a variety of design patterns and understanding them through real-world examples. This will entail a short explanation of the concept of design patterns and the original set of the 'Gang of Four' patterns, which will help you in structuring your designs efficiently. Next, you'll cover the most important 'anti-patterns' (essentially bad software development practices) to aid you in steering clear of problems during programming. You'll then learn about the eight most important patterns for each creational, structural, and behavioral type. After this, you'll be introduced to the concept of 'concurrency' patterns, which are design patterns specifically related to multithreading and parallel computation. These will enable you to develop and improve an interface between items and harmonize shared memories within threads. Toward the concluding chapters, you'll explore design patterns specific to program design and other categories of patterns that do not fall under the 'design' umbrella. By the end of this book, you'll be able to address common design problems encountered while developing applications and feel confident while building scalable projects. What you will learn * Gain insights into the concept of design patterns * Study modern programming techniques with Delphi * Keep up to date with the latest additions and program design techniques in Delphi * Get to grips with various modern multithreading approaches * Discover creational, structural, behavioral, and concurrent patterns * Determine how to break a design problem down into its component parts Who this book is for Hands-On Design Patterns with Delphi is aimed at beginner-level Delphi developers who want to build scalable and robust applications. Basic knowledge of Delphi is a must.

Unreal Engine 4 for virtual reality game design, development, User Experience design techniques and Blueprint programming to create virtual reality gameplay for HTC Vive, Oculus Rift, PSVR, and Windows Mixed Reality headsets. Key Features * Build VR games from scratch with the power of Unreal Engine 4 * Learn User Experience design practices to take your VR game to the next level * Understand the best practices to creating art for games on HTC Vive, Oculus Rift, and PSVR Book Description With the ability to put players directly in the game, virtual reality gives users the chance to experience digital worlds directly. Nevertheless, many designers are unsure where to start when working with this amazing technology. With this book, you will learn user experience design processes and create immersive gameplay experiences designed for entertainment and player comfort. Using the power of Unreal Engine 4’s Blueprint visual scripting language, you will build player interaction and locomotion systems from scratch and use these flexible systems to create a sample game, as well as develop functional 2D and 3D user interfaces for players to interact with. And also learn the best practices for creating game art for virtual reality. Finally, you will learn how to test your application with your target audience and finalize your game for distribution. By the end of this book, you will have the knowledge to be able to make the leap from traditional game development to creating immersive virtual reality experiences using Unreal Engine 4. What you will learn * Understand how to get started with VR development in Unreal Engine 4 * Design and create interaction and locomotion systems from scratch * Plan and program a sample game for VR * Understand how VR affects user experience and user interfaces * Discuss what is needed to create optimized art for VR * Test your game with users and prepare for distribution Who this book is for The audience for this book is intermediate or advanced users of Unreal Engine 4 but who have not begun working with VR technology. These users are familiar with the game engine and have an interest in VR technology. They are just beginning to explore the VR features that the game engine has to offer.

Grasp machine learning concepts, techniques, and algorithms with the help of real-world examples using Python libraries such as TensorFlow and scikit-learn Key Features * Exploit the power of Python to explore the world of data mining and data analytics * Discover machine learning algorithms to solve complex challenges faced by data scientists today * Use Python libraries such as TensorFlow and Keras to create smart cognitive actions for your projects Book Description The surge in interest in machine learning (ML) is due to the fact that it revolutionizes automation by learning patterns in data and using them to make predictions and decisions. If you’re interested in ML, this book will serve as your entry point to ML. Python Machine Learning By Example begins with an introduction to important ML concepts and implementations using Python libraries. Each chapter of the book walks you through an industry adopted application. You’ll implement ML techniques in areas such as exploratory data analysis, feature engineering, and natural language processing (NLP) in a clear and easy-to-follow way. With the help of this extended and updated edition, you’ll understand how to tackle data-driven problems and implement your solutions with the powerful yet simple Python language and popular Python packages and tools such as TensorFlow, scikit-learn, gensim, and Keras. To aid your understanding of popular ML algorithms, the book covers interesting and easy-to-follow examples such as news topic modeling and classification, spam email detection, stock price forecasting, and more. By the end of the book, you’ll have put together a broad picture of the ML ecosystem and will be well-versed with the best practices of applying ML techniques to make the most out of new opportunities. What you will learn * Understand the important concepts in machine learning and data science * Use Python to explore the world of data mining and analytics * Scale up model training using varied data complexities with Apache Spark * Delve deep into text and NLP using Python libraries such NLTK and gensim * Select and build an ML model and evaluate and optimize its performance * Implement ML algorithms from scratch in Python, TensorFlow, and scikit-learn Who this book is for If you’re a machine learning aspirant, data analyst, or data engineer highly passionate about machine learning and want to begin working on ML assignments, this book is for you. Prior knowledge of Python coding is assumed and basic familiarity with statistical concepts will be beneficial although not necessary.

Grasp advanced PowerShell Core 6.0 functionalities to automate your environment Key Features * Keep up with changes introduced in PowerShell Core 6.0 * Easily maintain appropriate compatibility with older versions * Automate complex tasks, manipulate data, and secure your environment with PowerShell Core 6.0 Book Description PowerShell scripts offer a handy way to automate various chores, however working effectively with these scripts can be a difficult task. This comprehensive guide starts with the fundamentals before moving on to advanced-level topics to help you become a PowerShell Core 6.0 expert. The first module, PowerShell Core 6.0 Fundamentals, begins with the new features of PowerShell Core 6.0, installing it on Linux, and working with parameters, objects and .NET classes from within PowerShell Core 6.0. As you make your way through the chapters, you'll see how to efficiently manage large amounts of data and interact with other services using PowerShell Core 6.0. You'll be able to make the most of PowerShell Core 6.0's powerful automation feature, where you will have different methods available to parse data and manipulate regular expressions and Windows Management Instrumentation (WMI). After having explored automation, you will enter the extending PowerShell Core 6.0 module, covering asynchronous processing and desired state configuration. In the last module, you will learn to extend PowerShell Core 6.0 using advanced scripts and filters, and also debug issues along with working on error handling techniques. By the end of this book, you will be an expert in scripting with PowerShell Core 6.0. What you will learn * Optimize code through the use of functions, switches, and looping structures * Work with objects and operators to test and manipulate data * Parse and manipulate different data types * Create scripts and functions using PowerShell * Use jobs, events, and popular public modules which assist with implementing multithreading * Write .NET classes with ease within the PowerShell * Create and implement regular expressions in PowerShell scripts * Make use of advanced techniques to define and restrict the behavior of parameters Who this book is for If you are a system administrator who wants to become an expert in controlling and automating your Windows environment, then Mastering Windows PowerShell Scripting is for you. It is also ideal for those new to the PowerShell language.

Discover the skill-sets required to implement various approaches to Machine Learning with Python Key Features * Explore unsupervised learning with clustering, autoencoders, restricted Boltzmann machines, and more * Build your own neural network models using modern Python libraries * Practical examples show you how to implement different machine learning and deep learning techniques Book Description Unsupervised learning is about making use of raw, untagged data and applying learning algorithms to it to help a machine predict its outcome. With this book, you will explore the concept of unsupervised learning to cluster large sets of data and analyze them repeatedly until the desired outcome is found using Python. This book starts with the key differences between supervised, unsupervised, and semi-supervised learning. You will be introduced to the best-used libraries and frameworks from the Python ecosystem and address unsupervised learning in both the machine learning and deep learning domains. You will explore various algorithms, techniques that are used to implement unsupervised learning in real-world use cases. You will learn a variety of unsupervised learning approaches, including randomized optimization, clustering, feature selection and transformation, and information theory. You will get hands-on experience with how neural networks can be employed in unsupervised scenarios. You will also explore the steps involved in building and training a GAN in order to process images. By the end of this book, you will have learned the art of unsupervised learning for different real-world challenges. What you will learn * Use cluster algorithms to identify and optimize natural groups of data * Explore advanced non-linear and hierarchical clustering in action * Soft label assignments for fuzzy c-means and Gaussian mixture models * Detect anomalies through density estimation * Perform principal component analysis using neural network models * Create unsupervised models using GANs Who this book is for This book is intended for statisticians, data scientists, machine learning developers, and deep learning practitioners who want to build smart applications by implementing key building block unsupervised learning, and master all the new techniques and algorithms offered in machine learning and deep learning using real-world examples. Some prior knowledge of machine learning concepts and statistics is desirable.

Explore various Generative Adversarial Network architectures using the Python ecosystem Key Features * Use different datasets to build advanced projects in the Generative Adversarial Network domain * Implement projects ranging from generating 3D shapes to a face aging application * Explore the power of GANs to contribute in open source research and projects Book Description Generative Adversarial Networks (GANs) have the potential to build next-generation models, as they can mimic any distribution of data. Major research and development work is being undertaken in this field since it is one of the rapidly growing areas of machine learning. This book will test unsupervised techniques for training neural networks as you build seven end-to-end projects in the GAN domain. Generative Adversarial Network Projects begins by covering the concepts, tools, and libraries that you will use to build efficient projects. You will also use a variety of datasets for the different projects covered in the book. The level of complexity of the operations required increases with every chapter, helping you get to grips with using GANs. You will cover popular approaches such as 3D-GAN, DCGAN, StackGAN, and CycleGAN, and you’ll gain an understanding of the architecture and functioning of generative models through their practical implementation. By the end of this book, you will be ready to build, train, and optimize your own end-to-end GAN models at work or in your own projects. What you will learn * Train a network on the 3D ShapeNet dataset to generate realistic shapes * Generate anime characters using the Keras implementation of DCGAN * Implement an SRGAN network to generate high-resolution images * Train Age-cGAN on Wiki-Cropped images to improve face verification * Use Conditional GANs for image-to-image translation * Understand the generator and discriminator implementations of StackGAN in Keras Who this book is for If you’re a data scientist, machine learning developer, deep learning practitioner, or AI enthusiast looking for a project guide to test your knowledge and expertise in building real-world GANs models, this book is for you.

Build effective RESTful APIs for enterprise with design patterns and REST framework’s out-of-the-box capabilities Key Features * Understand advanced topics such as API gateways, API securities, and cloud * Implement patterns programmatically with easy-to-follow examples * Modernize legacy codebase using API connectors, layers, and microservices Book Description This book deals with the Representational State Transfer (REST) paradigm, which is an architectural style that allows networked devices to communicate with each other over the internet. With the help of this book, you’ll explore the concepts of service-oriented architecture (SOA), event-driven architecture (EDA), and resource-oriented architecture (ROA). This book covers why there is an insistence for high-quality APIs toward enterprise integration. It also covers how to optimize and explore endpoints for microservices with API gateways and touches upon integrated platforms and Hubs for RESTful APIs. You’ll also understand how application delivery and deployments can be simplified and streamlined in the REST world. The book will help you dig deeper into the distinct contributions of RESTful services for IoT analytics and applications. Besides detailing the API design and development aspects, this book will assist you in designing and developing production-ready, testable, sustainable, and enterprise-grade APIs. By the end of the book, you’ll be empowered with all that you need to create highly flexible APIs for next-generation RESTful services and applications. What you will learn * Explore RESTful concepts, including URI, HATEOAS, and Code on Demand * Study core patterns like Statelessness, Pagination, and Discoverability * Optimize endpoints for linked microservices with API gateways * Delve into API authentication, authorization, and API security implementations * Work with Service Orchestration to craft composite and process-aware services * Expose RESTful protocol-based APIs for cloud computing Who this book is for This book is primarily for web, mobile, and cloud services developers, architects, and consultants who want to build well-designed APIs for creating and sustaining enterprise-class applications. You’ll also benefit from this book if you want to understand the finer details of RESTful APIs and their design techniques along with some tricks and tips.

Over 70 recipes to effectively apply DevOps best practices and implement Agile, Git, CI-CD & Test automation using Azure DevOps Server (TFS) 2019 Key Features * Learn improving code quality using pull requests, branch policies, githooks and git branching design * Accelerate the deployment of high quality software by automating build and releases using CI-CD Pipelines. * Learn tried and tested techniques to automate database deployments, App Service & Function Deployments in Azure. Book Description Azure DevOps Server, previously known as Team Foundation Server (TFS), is a comprehensive on-premise DevOps toolset with a rich ecosystem of open source plugins. This book is your one stop guide to learn how to effectively use all of these Azure DevOps services to go from zero to DevOps. You will start by building high-quality scalable software targeting .NET, .NET core or Node.js applications. You will learn techniques that will help you to set up end-to-end traceability of your code changes from design through to release. Whether you are deploying software on-premise or in the cloud in App Service, Functions, or Azure VMs, this book will help you learn release management techniques to reduce release failures. Next, you will be able to secure application configuration by using Azure KeyVault. You will also learn how to create and release extensions to the Azure DevOps marketplace and reach million developer ecosystem for feedback. The working extension samples will allow you to iterate changes in your extensions easily and release updates to the marketplace quickly. By the end of this book, techniques provided in the book will help you break down the invisible silos between your software development teams. This will transform you from being a good software development team to an elite modern cross functional software development team. What you will learn * Set up a team project for an Agile delivery team, importing requirements from Excel * Plan,track, and monitor progress using self updating boards, Sprint and Kanban boards * Unlock the features of Git by using branch policies, Git pull requests, forks, and Git hooks * Build and release .NET core, SQL and Node.js applications using Azure Pipeline * Automate testing by integrating Microsoft and open source testing frameworks * Extend Azure DevOps Server to a million developer ecosystem Who this book is for This book is for anyone looking to succeed with DevOps. The techniques in this book apply to all roles of the software development lifecycle including developers, testers, architects, configuration analysts, site reliability engineers and release managers. If you are a new user you’ll learn how to get started; if you are an experienced user you’ll learn how to launch your project into a modern and mature DevOps enabled software development team.

Explore modern game programming and rendering techniques to build games using C++ programming language and its popular libraries Key Features * Learn how you can build basic 2D and complex 3D games with C++ * Understand shadows, texturing, lighting, and rendering in 3D game development using OpenGL * Uncover modern graphics programming techniques and GPU compute methods using the Vulkan API Book Description Although numerous languages are currently being used to develop games, C++ remains the standard for fabricating expert libraries and tool chains for game development. This book introduces you to the world of game development with C++. C++ Game Development By Example starts by touching upon the basic concepts of math, programming, and computer graphics and creating a simple side-scrolling action 2D game. You'll build a solid foundation by studying basic game concepts such as creating game loops, rendering 2D game scenes using SFML, 2D sprite creation and animation, and collision detection. The book will help you advance to creating a 3D physics puzzle game using modern OpenGL and the Bullet physics engine. You'll understand the graphics pipeline, which entails creating 3D objects using vertex and index buffers and rendering them to the scene using vertex and fragment shaders. Finally, you'll create a basic project using the Vulkan library that'll help you get to grips with creating swap chains, image views, render passes, and frame buffers for building high-performance graphics in your games. By the end of this book, you’ll be ready with 3 compelling projects created with SFML, the Vulkan API, and OpenGL, and you'll be able take your game and graphics programming skills to the next level. What you will learn * Understand shaders and how to write a basic vertex and fragment shader * Build a Visual Studio project and add SFML to it * Discover how to create sprite animations and a game character class * Add sound effects and background music to your game * Grasp how to integrate Vulkan into Visual Studio * Create shaders and convert them to the SPIR-V binary format Who this book is for If you’re a developer keen to learn game development with C++ or get up to date with game development, this book is for you. Some knowledge of C++ programming is assumed.

Explore the power of D3.js 5 and its integration with web technologies for building rich and interactive data visualization solutions Key Features * Explore the latest D3.js 5 for creating charts, plots, and force-directed graphics * Practical guide for creating interactive graphics and data-driven apps with JavaScript * Build Real-time visualization and transition on web using SVG with D3.js Book Description This book is a practical hands-on introduction to D3 (Data-driven Documents): the most popular open-source JavaScript library for creating interactive web-based data visualizations. Based entirely on open web standards, D3 provides an integrated collection of tools for efficiently binding data to graphical elements. If you have basic knowledge of HTML, CSS and JavaScript you can use D3.js to create beautiful interactive web-based data visualizations. D3 is not a charting library. It doesn’t contain any pre-defined chart types, but can be used to create whatever visual representations of data you can imagine. The goal of this book is to introduce D3 and provide a learning path so that you obtain a solid understanding of its fundamental concepts, learn to use most of its modules and functions, and gain enough experience to create your own D3 visualizations. You will learn how to create bar, line, pie and scatter charts, trees, dendograms, treemaps, circle packs, chord/ribbon diagrams, sankey diagrams, animated network diagrams, and maps using different geographical projections. Fundamental concepts are explained in each chapter and then applied to a larger example in step-by-step tutorials, complete with full code, from hundreds of examples you can download and run. This book covers D3 version 5 and is based on ES2015 JavaScript. What you will learn * Learn to use D3.js version 5 and web standards to create beautiful interactive data-driven visualizations for the web * Bind data to DOM elements, applying different scales, color schemes and configuring smooth animated transitions for data updates * Generate data structures and layouts for many popular chart formats * Apply interactive behaviors to any chart * Create thematic maps based on GIS data using different geographical projections with interactive behaviors * Load, parse and transform data from JSON and CSV formats Who this book is for The book is intended for web developers, web designers, data scientists, artists, and any developer who wish to create interactive data visualization for the Web using D3. The book assumes basic knowledge of HTML, CSs, and JavaScript.

This is a practical certification guide covering all the exam topics in an easy-to-follow manner backed with self-assessment scenarios for better preparation. Key Features *A step-by-step guide to give you a clear understanding of the Network+ Certification *Learn about network architecture, protocols, security, and network troubleshooting *Confidently ace the N10-007 exam with the help of practice tests Book Description CompTIA certified professionals have always had the upper hand in the information technology industry. This book will be your ideal guide to efficiently passing and achieving this certification. Learn from industry experts and implement their practices to resolve complex IT issues. This book revolves around networking concepts where readers will learn topics like network architecture, security, network monitoring, and troubleshooting. This book will not only prepare the readers conceptually but will also help them pass the N10-007 exam. This guide will also provide practice exercise after every chapter where readers can ensure their concepts are clear. By the end of this book, readers will leverage this guide and the included practice questions to boost their confidence in appearing for the actual certificate. What you will learn *Explain the purpose of a variety of networking concepts and implement them appropriately *Understand physical security and common attacks while securing wired and wireless networks *Understand the fundamentals of IPv4 and IPv6 *Determine and explain the appropriate cabling, device, and storage technologies *Understand network troubleshooting methodology and appropriate tools to support connectivity and performance *Use best practices to manage the network, determine policies, and ensure business continuity Who this book is for This book is ideal for readers wanting to pass the CompTIA Network+ certificate. Rookie network engineers and system administrators interested in enhancing their networking skills would also benefit from this book. No Prior knowledge on networking would be needed.

Begin your iOS 12 app development journey with this practical guide Key Features *Kick-start your iOS programming career and have fun building iOS apps of your choice *Get to grips with Xcode 10 and Swift 4.2, the building blocks of iOS development *Discover the latest features of iOS 12 - SiriKit, notifications, and much more Book Description Want to build iOS 12 applications from scratch with the latest Swift 4.2 language and Xcode 10 by your side? Forget sifting through tutorials and blog posts; this book is a direct route to iOS development, taking you through the basics and showing you how to put principles into practice. Take advantage of this developer-friendly guide and start building applications that may just take the App Store by storm! If you’re already an experienced programmer, you can jump right in and learn the latest iOS 12 features. For beginners, this book starts by introducing you to iOS development as you learn Xcode and Swift. You'll also study advanced iOS design topics, such as gestures and animations, to give your app the edge. You’ll explore the latest Swift 4.2 and iOS 12 developments by incorporating new features, such as the latest in notifications, custom-UI notifications, maps, and the recent additions in Sirikit. The book will guide you in using TestFlight to quickly get to grips with everything you need to get your project on the App Store. By the end of this book, you'll be ready to start building your own cool iOS applications confidently. What you will learn *Explore the distinctive design principles that define the iOS user experience *Navigate panels within an Xcode project *Use the latest Xcode asset catalogue of Xcode 10 *Create a playgrounds project within your projects and understand how Ranges and Control flow work *Study operations with integers and work your way through if statements *Build a responsive UI and add privacy to your custom-rich notifications *Set up Sirikit to add voice for Siri shortcuts *Collect valuable feedback with TestFlight before releasing your apps on the App Store Who this book is for This book is for you if you are completely new to Swift, iOS, or programming and want to make iOS applications. However, you’ll also find this book useful if you’re an experienced programmer looking to explore the latest iOS 12 features.

Don't waste your energy thinking about servers; use AWS to build enterprise-grade serverless applications. Key Features *Learn how to quickly and easily go serverless *Explore AWS and Lambda: the first building blocks of serverless applications on AWS *Study different approaches to deploy and maintain serverless applications Book Description Serverless Architecture with AWS begins with an introduction to the serverless model and helps you get started with AWS and Lambda. You'll also get to grips with other capabilities of the AWS Serverless Platform and see how AWS supports enterprise-grade serverless applications with and without Lambda. This book will guide you in deploying your first serverless project and exploring the capabilities of serverless Amazon Athena, an interactive query service that makes it easy to analyze data in Amazon Simple Storage Service (S3 Amazon) using standard SQL. You’ll also learn about AWS Glue, a fully managed ETL service that makes categorizing data easy and cost-effective. You'll study how Amazon Kinesis makes it possible to unleash the potential of real-time data insights and analytics with capabilities such as video streams, data streams, data firehose, and data analytics. Last but not least, you’ll be equipped to combine Amazon Kinesis capabilities with AWS Lambda to create lightweight serverless architectures. By the end of the book, you will be ready to create and run your first serverless application that takes advantage of the high availability, security, performance, and scalability of AWS. What you will learn *Explore AWS services for supporting a serverless environment *Set up AWS services to make applications scalable and highly available *Deploy a static website with a serverless architecture *Build your first serverless web application *Study the changes in a deployed serverless web application *Apply best practices to ensure overall security, availability, and reliability Who this book is for This book is for you if you want to develop serverless applications and have some prior coding experience. Though no prior experience of AWS is needed, basic knowledge of Java or Node.js will be an added advantage.

Master shell basics and Unix tools and discover easy commands to perform complex tasks with speed Key Features *Learn why the Bash shell is widely used on Linux and iOS *Explore advanced shell concepts, such as pipes and redirection *Understand how to use Unix command-line tools as building blocks for different tasks Book Description The most basic interface to a computer—the command line—remains the most flexible and powerful way of processing data and performing and automating various day-to-day tasks. Command Line Fundamentals begins by exploring the basics, and then focuses on the most common tool, the Bash shell (which is standard on all Linux and iOS systems). As you make your way through the book, you'll explore the traditional Unix command-line programs as implemented by the GNU project. You'll also learn to use redirection and pipelines to assemble these programs to solve complex problems. By the end of this book, you'll have explored the basics of shell scripting, allowing you to easily and quickly automate tasks. What you will learn *Use the Bash shell to run commands *Utilize basic Unix utilities such as cat, tr, sort, and uniq *Explore shell wildcards to manage groups of files *Apply useful keyboard shortcuts in shell *Employ redirection and pipes to process data *Write both basic and advanced shell scripts to automate tasks Who this book is for Command Line Fundamentals is for programmers who use GUIs but want to understand how to use the command line to complete tasks faster.

Build efficient data flow and machine learning programs with this flexible, multi-functional open-source cluster-computing framework Key Features *Master the art of real-time big data processing and machine learning *Explore a wide range of use-cases to analyze large data *Discover ways to optimize your work by using many features of Spark 2.x and Scala Book Description Apache Spark is an in-memory, cluster-based data processing system that provides a wide range of functionalities such as big data processing, analytics, machine learning, and more. With this Learning Path, you can take your knowledge of Apache Spark to the next level by learning how to expand Spark's functionality and building your own data flow and machine learning programs on this platform. You will work with the different modules in Apache Spark, such as interactive querying with Spark SQL, using DataFrames and datasets, implementing streaming analytics with Spark Streaming, and applying machine learning and deep learning techniques on Spark using MLlib and various external tools. By the end of this elaborately designed Learning Path, you will have all the knowledge you need to master Apache Spark, and build your own big data processing and analytics pipeline quickly and without any hassle. This Learning Path includes content from the following Packt products: *Mastering Apache Spark 2.x by Romeo Kienzler *Scala and Spark for Big Data Analytics by Md. Rezaul Karim, Sridhar Alla *Apache Spark 2.x Machine Learning Cookbook by Siamak Amirghodsi, Meenakshi Rajendran, Broderick Hall, Shuen MeiCookbook What you will learn *Get to grips with all the features of Apache Spark 2.x *Perform highly optimized real-time big data processing *Use ML and DL techniques with Spark MLlib and third-party tools *Analyze structured and unstructured data using SparkSQL and GraphX *Understand tuning, debugging, and monitoring of big data applications *Build scalable and fault-tolerant streaming applications *Develop scalable recommendation engines Who this book is for If you are an intermediate-level Spark developer looking to master the advanced capabilities and use-cases of Apache Spark 2.x, this Learning Path is ideal for you. Big data professionals who want to learn how to integrate and use the features of Apache Spark and build a strong big data pipeline will also find this Learning Path useful. To grasp the concepts explained in this Learning Path, you must know the fundamentals of Apache Spark and Scala.

A step-by-step guide that demonstrates how to build simple-to-advanced applications through examples in Julia Lang 1.x using modern tools Key Features *Work with powerful open-source libraries for data wrangling, analysis, and visualization *Develop full-featured, full-stack web applications *Learn to perform supervised and unsupervised machine learning and time series analysis with Julia Book Description Julia is a new programming language that offers a unique combination of performance and productivity. Its powerful features, friendly syntax, and speed are attracting a growing number of adopters from Python, R, and Matlab, effectively raising the bar for modern general and scientific computing. After six years in the making, Julia has reached version 1.0. Now is the perfect time to learn it, due to its large-scale adoption across a wide range of domains, including fintech, biotech, education, and AI. Beginning with an introduction to the language, Julia Programming Projects goes on to illustrate how to analyze the Iris dataset using DataFrames. You will explore functions and the type system, methods, and multiple dispatch while building a web scraper and a web app. Next, you'll delve into machine learning, where you'll build a books recommender system. You will also see how to apply unsupervised machine learning to perform clustering on the San Francisco business database. After metaprogramming, the final chapters will discuss dates and time, time series analysis, visualization, and forecasting. We'll close with package development, documenting, testing and benchmarking. By the end of the book, you will have gained the practical knowledge to build real-world applications in Julia. What you will learn *Leverage Julia's strengths, its top packages, and main IDE options *Analyze and manipulate datasets using Julia and DataFrames *Write complex code while building real-life Julia applications *Develop and run a web app using Julia and the HTTP package *Build a recommender system using supervised machine learning *Perform exploratory data analysis *Apply unsupervised machine learning algorithms *Perform time series data analysis, visualization, and forecasting Who this book is for Data scientists, statisticians, business analysts, and developers who are interested in learning how to use Julia to crunch numbers, analyze data and build apps will find this book useful. A basic knowledge of programming is assumed.

Combine advanced analytics including Machine Learning, Deep Learning Neural Networks and Natural Language Processing with modern scalable technologies including Apache Spark to derive actionable insights from Big Data in real-time Key Features *Make a hands-on start in the fields of Big Data, Distributed Technologies and Machine Learning *Learn how to design, develop and interpret the results of common Machine Learning algorithms *Uncover hidden patterns in your data in order to derive real actionable insights and business value Book Description Every person and every organization in the world manages data, whether they realize it or not. Data is used to describe the world around us and can be used for almost any purpose, from analyzing consumer habits to fighting disease and serious organized crime. Ultimately, we manage data in order to derive value from it, and many organizations around the world have traditionally invested in technology to help process their data faster and more efficiently. But we now live in an interconnected world driven by mass data creation and consumption where data is no longer rows and columns restricted to a spreadsheet, but an organic and evolving asset in its own right. With this realization comes major challenges for organizations: how do we manage the sheer size of data being created every second (think not only spreadsheets and databases, but also social media posts, images, videos, music, blogs and so on)? And once we can manage all of this data, how do we derive real value from it? The focus of Machine Learning with Apache Spark is to help us answer these questions in a hands-on manner. We introduce the latest scalable technologies to help us manage and process big data. We then introduce advanced analytical algorithms applied to real-world use cases in order to uncover patterns, derive actionable insights, and learn from this big data. What you will learn *Understand how Spark fits in the context of the big data ecosystem *Understand how to deploy and configure a local development environment using Apache Spark *Understand how to design supervised and unsupervised learning models *Build models to perform NLP, deep learning, and cognitive services using Spark ML libraries *Design real-time machine learning pipelines in Apache Spark *Become familiar with advanced techniques for processing a large volume of data by applying machine learning algorithms Who this book is for This book is aimed at Business Analysts, Data Analysts and Data Scientists who wish to make a hands-on start in order to take advantage of modern Big Data technologies combined with Advanced Analytics.

Process large volumes of data in real-time while building high performance and robust data stream processing pipeline using the latest Apache Kafka 2.0 Key Features *Solve practical large data and processing challenges with Kafka *Tackle data processing challenges like late events, windowing, and watermarking *Understand real-time streaming applications processing using Schema registry, Kafka connect, Kafka streams, and KSQL Book Description Apache Kafka is a great open source platform for handling your real-time data pipeline to ensure high-speed filtering and pattern matching on the ?y. In this book, you will learn how to use Apache Kafka for efficient processing of distributed applications and will get familiar with solving everyday problems in fast data and processing pipelines. This book focuses on programming rather than the configuration management of Kafka clusters or DevOps. It starts off with the installation and setting up the development environment, before quickly moving on to performing fundamental messaging operations such as validation and enrichment. Here you will learn about message composition with pure Kafka API and Kafka Streams. You will look into the transformation of messages in different formats, such asext, binary, XML, JSON, and AVRO. Next, you will learn how to expose the schemas contained in Kafka with the Schema Registry. You will then learn how to work with all relevant connectors with Kafka Connect. While working with Kafka Streams, you will perform various interesting operations on streams, such as windowing, joins, and aggregations. Finally, through KSQL, you will learn how to retrieve, insert, modify, and delete data streams, and how to manipulate watermarks and windows. What you will learn *How to validate data with Kafka *Add information to existing data ?ows *Generate new information through message composition *Perform data validation and versioning with the Schema Registry *How to perform message Serialization and Deserialization *How to perform message Serialization and Deserialization *Process data streams with Kafka Streams *Understand the duality between tables and streams with KSQL Who this book is for This book is for developers who want to quickly master the practical concepts behind Apache Kafka. The audience need not have come across Apache Kafka previously; however, a familiarity of Java or any JVM language will be helpful in understanding the code in this book.

Gain a working knowledge of advanced machine learning and explore Python’s powerful tools for extracting data from images and videos Key Features *Implement image classification and object detection using machine learning and deep learning *Perform image classification, object detection, image segmentation, and other Computer Vision tasks *Crisp content with a practical approach to solving real-world problems in Computer Vision Book Description Python is the ideal programming language for rapidly prototyping and developing production-grade codes for image processing and Computer Vision with its robust syntax and wealth of powerful libraries. This book will help you design and develop production-grade Computer Vision projects tackling real-world problems. With the help of this book, you will learn how to set up Anaconda and Python for the major OSes with cutting-edge third-party libraries for Computer Vision. You'll learn state-of-the-art techniques for classifying images, finding and identifying human postures, and detecting faces within videos. You will use powerful machine learning tools such as OpenCV, Dlib, and TensorFlow to build exciting projects such as classifying handwritten digits, detecting facial features,and much more. The book also covers some advanced projects, such as reading text from license plates from real-world images using Google’s Tesseract software, and tracking human body poses using DeeperCut within TensorFlow. By the end of this book, you will have the expertise required to build your own Computer Vision projects using Python and its associated libraries. What you will learn *Install and run major Computer Vision packages within Python *Apply powerful support vector machines for simple digit classification *Understand deep learning with TensorFlow *Build a deep learning classifier for general images *Use LSTMs for automated image captioning *Read text from real-world images *Extract human pose data from images Who this book is for Python programmers and machine learning developers who wish to build exciting Computer Vision projects using the power of machine learning and OpenCV will find this book useful. The only prerequisite for this book is that you should have a sound knowledge of Python programming.

Simplify next-generation deep learning by implementing powerful generative models using Python, TensorFlow and Keras Key Features *Understand the common architecture of different types of GANs *Train, optimize, and deploy GAN applications using TensorFlow and Keras *Build generative models with real-world data sets, including 2D and 3D data Book Description Developing Generative Adversarial Networks (GANs) is a complex task, and it is often hard to find code that is easy to understand. This book leads you through eight different examples of modern GAN implementations, including CycleGAN, simGAN, DCGAN, and 2D image to 3D model generation. Each chapter contains useful recipes to build on a common architecture in Python, TensorFlow and Keras to explore increasingly difficult GAN architectures in an easy-to-read format. The book starts by covering the different types of GAN architecture to help you understand how the model works. This book also contains intuitive recipes to help you work with use cases involving DCGAN, Pix2Pix, and so on. To understand these complex applications, you will take different real-world data sets and put them to use. By the end of this book, you will be equipped to deal with the challenges and issues that you may face while working with GAN models, thanks to easy-to-follow code solutions that you can implement right away. What you will learn *Structure a GAN architecture in pseudocode *Understand the common architecture for each of the GAN models you will build *Implement different GAN architectures in TensorFlow and Keras *Use different datasets to enable neural network functionality in GAN models *Combine different GAN models and learn how to fine-tune them *Produce a model that can take 2D images and produce 3D models *Develop a GAN to do style transfer with Pix2Pix Who this book is for This book is for data scientists, machine learning developers, and deep learning practitioners looking for a quick reference to tackle challenges and tasks in the GAN domain. Familiarity with machine learning concepts and working knowledge of Python programming language will help you get the most out of the book.