Superspy Anna Resnikov is back in Alex Dryden's latest, masterful international thriller—The Blind SpyRussia has never accepted Ukraine's independence and now the Patrioti—Putin, his elder statesmen, and seasoned generals dedicated to rebuilding their fallen empire—are using the KGB's controversial elite and clandestine forces of Department S to destabilize the young democratic nation and bring it back under Russian control.But Cougar, the powerful private intelligence company that overshadows even the CIA in its reach, learns of Russia's plans and strikes at the heart of its plot with its own lethal weapon—the gorgeous ex–KGB colonel Anna Resnikov. More than a gifted spy and expert killer, Anna lost the love of her life and the father of her child at the hands of her former countrymen. Her defection to Cougar has made her the most wanted woman in Russia, but she'll risk any danger to herself for the chance to destroy the evil that rules her homeland. And on the ground in Ukraine, she meets a formidable foe, a mysterious KGB spy whose aims are suspiciously unclear but whose power is unmistakably deadly.New York Times bestselling author James Grippando raves, "Alex Dryden...can please everyone from fans of old le Carré to students of current affairs." The Blind Spy is another killer cocktail of page-turning suspense, high-octane action, and riveting intrigue that will hold you captive from beginning to end.

An unexpected treasure: A long-lost novel of innocence threatened, by the author of the beloved classic The Moonflower VineThe time: 1941, at the cusp of America's entry into World War II. The place: southwest Missouri, on the edge of the Ozark Mountains. A young single woman named Allen Liles has taken a job as a junior college teacher in a small town, although she dreams of living in New York City, of dancing at recitals, of absorbing the bohemian delights of the Village. Then she encounters two young men: George, a lanky, carefree spirit, and Toby, a dark-haired, searching soul with a wary look in his eyes. Soon the three strike up an after-school friendship, bantering and debating over letters, ethics, and philosophy—innocently at first, but soon in giddy flirtation—until Allen and one of the young men push things too far, and the quiet happiness she has struggled so hard to discover is thrown into jeopardy.

Life After Kes examines the history and legacy of the 1969 award-winning British film, Kes, about a boy's (Billy Casper) relationship with a kestrel. This fascinating book not only pays homage to the vision and extraordinary talent involved both in front and behind the camera but also looks at subsequent changes in the educational system, posing some important questions. Are we any better off today? Have schools and teaching staff moved forward over the last few decades? Have successive government's learnt anything from the mistakes of the past? Life After Kes explores the lives of the cast and production team since the making of the film including David (Dai) Bradley who played the lead role and examines why the legacy of Billy Casper and the national perception of Kes cast a shadow over South Yorkshire. Does Casper's ghost still haunt this ex-mining community and is director Ken Loach's gritty northern drama as relevant today as it was then? This book is a must-have for all film fans, anyone who enjoyed Kes and all those with an interest in British social history.

A comprehensive guide with extensive coverage on concepts such as OOP, functional programming, generic programming, and STL along with the latest features of C++ Key Features * Delve into the core patterns and components of C++ in order to master application design * Learn tricks, techniques, and best practices to solve common design and architectural challenges * Understand the limitation imposed by C++ and how to solve them using design patterns Book Description C++ is a general-purpose programming language designed with the goals of efficiency, performance, and flexibility in mind. Design patterns are commonly accepted solutions to well-recognized design problems. In essence, they are a library of reusable components, only for software architecture, and not for a concrete implementation. The focus of this book is on the design patterns that naturally lend themselves to the needs of a C++ programmer, and on the patterns that uniquely benefit from the features of C++, in particular, the generic programming. Armed with the knowledge of these patterns, you will spend less time searching for a solution to a common problem and be familiar with the solutions developed from experience, as well as their advantages and drawbacks. The other use of design patterns is as a concise and an efficient way to communicate. A pattern is a familiar and instantly recognizable solution to specific problem; through its use, sometimes with a single line of code, we can convey a considerable amount of information. The code conveys: "This is the problem we are facing, these are additional considerations that are most important in our case; hence, the following well-known solution was chosen." By the end of this book, you will have gained a comprehensive understanding of design patterns to create robust, reusable, and maintainable code. What you will learn * Recognize the most common design patterns used in C++ * Understand how to use C++ generic programming to solve common design problems * Explore the most powerful C++ idioms, their strengths, and drawbacks * Rediscover how to use popular C++ idioms with generic programming * Understand the impact of design patterns on the program’s performance Who this book is for This book is for experienced C++ developers and programmers who wish to learn about software design patterns and principles and apply them to create robust, reusable, and easily maintainable apps.

Mick Abrahams first rose to fame as a guitarist during the 1960s and was a founder member of Jethro Tull, although his time with the band was to prove short lived owing to the vividly contrasting musical styles of himself and Ian Anderson. In his autobiography What is a Wommett Mick finally puts the record straight about this parting of the ways and the events that have shaped the man and his music since that time up to the present day. Perhaps best known for his time with Blodwyn Pig, the band he formed after leaving Tull, Abrahams has continued to delight fans with his own brand of blues, jazz and rock on highly acclaimed albums spanning several decades. With a fitting foreword by radio presenter and champion of great music, Bob Harris, this autobiography provides a fascinating insight into the character of an upbeat man who hasn't allowed anything to keep him down for long. Packed with anecdotes and stories about Mick's life in and out of the spotlight, this book is a must have for his fans and anyone who remembers the excitement of the emerging new musical talent of the sixties.

Integrate your React applications with React to build efficient web services. Key Features * Learn React by building applications with Create React App * Create interactive UIs exploring the latest feature of CRA 2.0 * Build Progressive Web Applications for a more seamless web Book Description If you're a power user and you aren’t happy always reusing default configurations, from previous applications with each new application, then all you need is Create React App (CRA), a tool in the React ecosystem designed to help you create boilerplate code for building a web frontend. This book will help you use CRA to write React programs without significant configuration-related difficulties. With this quick start guide, you will integrate your applications with React to build efficient professional web services.You will learn to design UIs with the features of CRA and template your React applications. By the end of the book, you will be sufficiently skilled to be able to build faster and effective React apps using CRA. What you will learn * Become familiar with React by building applications with Create React App * Make your frontend development hassle free * Create interactive UIs exploring the latest features of CRA 2 * Build modern, React projects with, SASS,and progressive web applications * Develop proxy backend servers and simulate interaction with a full backend * Keep your application fully tested and maintain confidence in your project Who this book is for The book is intended for the web developers who want to jump into building great frontend with React using easy templating solutions.

Build your Machine Learning portfolio by creating 6 cutting-edge Artificial Intelligence projects using neural networks in Python Key Features * Discover neural network architectures (like CNN and LSTM) that are driving recent advancements in AI * Build expert neural networks in Python using popular libraries such as Keras * Includes projects such as object detection, face identification, sentiment analysis, and more Book Description Neural networks are at the core of recent AI advances, providing some of the best resolutions to many real-world problems, including image recognition, medical diagnosis, text analysis, and more. This book goes through some basic neural network and deep learning concepts, as well as some popular libraries in Python for implementing them. It contains practical demonstrations of neural networks in domains such as fare prediction, image classification, sentiment analysis, and more. In each case, the book provides a problem statement, the specific neural network architecture required to tackle that problem, the reasoning behind the algorithm used, and the associated Python code to implement the solution from scratch. In the process, you will gain hands-on experience with using popular Python libraries such as Keras to build and train your own neural networks from scratch. By the end of this book, you will have mastered the different neural network architectures and created cutting-edge AI projects in Python that will immediately strengthen your machine learning portfolio. What you will learn * Learn various neural network architectures and its advancements in AI * Master deep learning in Python by building and training neural network * Master neural networks for regression and classification * Discover convolutional neural networks for image recognition * Learn sentiment analysis on textual data using Long Short-Term Memory * Build and train a highly accurate facial recognition security system Who this book is for This book is a perfect match for data scientists, machine learning engineers, and deep learning enthusiasts who wish to create practical neural network projects in Python. Readers should already have some basic knowledge of machine learning and neural networks.

Ronnie Biggs: The Inside Story, written by two of Ronnie Biggs's closest friends and most ardent supporters, delivers exactly what it says on the label, giving a very personal, unique and yet disturbing insight into the mind and subsequent treatment by the judicial and penal systems of the man that became a legendary household name for his role in one of Britain's most notorious crimes, the Great Train Robbery of 1963, and his subsequent life on the run upon his escape from prison in 1965. Raising pointed questions and dispelling many myths, the story makes one wonder who is the greater criminal: the carpenter that played a bit part in an unarmed robbery 45 years ago, who has remained incarcerated since his return to the UK in 2001 despite the fact that he is now a frail, wheelchair-bound 79-year-old grandfather who is no threat to society, is fed via a tube to his stomach and can only communicate by pointing to letters on a laminated sheet; or the justice and prison systems that have allowed him to rot in jail for so long. One thing's for sure, although Ronnie Biggs's body is letting him down after a series of strokes and other illnesses, his legal team, campaign supporters, underworld friends and devoted family certainly aren't, and neither is his own fighting spirit or his humanity in the face of inhumanity. All he wants now is to be able to die a free man rather than suffer "e;a slow crucifixion on the Home Office cross"e;, and once all the facts have been digested one can only be moved to ask: "e;How could anyone deny him that?"e;

Understand how to apply distributed tracing to microservices-based architectures Key Features * A thorough conceptual introduction to distributed tracing * An exploration of the most important open standards in the space * A how-to guide for code instrumentation and operating a tracing infrastructure Book Description Mastering Distributed Tracing will equip you to operate and enhance your own tracing infrastructure. Through practical exercises and code examples, you will learn how end-to-end tracing can be used as a powerful application performance management and comprehension tool. The rise of Internet-scale companies, like Google and Amazon, ushered in a new era of distributed systems operating on thousands of nodes across multiple data centers. Microservices increased that complexity, often exponentially. It is harder to debug these systems, track down failures, detect bottlenecks, or even simply understand what is going on. Distributed tracing focuses on solving these problems for complex distributed systems. Today, tracing standards have developed and we have much faster systems, making instrumentation less intrusive and data more valuable. Yuri Shkuro, the creator of Jaeger, a popular open-source distributed tracing system, delivers end-to-end coverage of the field in Mastering Distributed Tracing. Review the history and theoretical foundations of tracing; solve the data gathering problem through code instrumentation, with open standards like OpenTracing, W3C Trace Context, and OpenCensus; and discuss the benefits and applications of a distributed tracing infrastructure for understanding, and profiling, complex systems. What you will learn * How to get started with using a distributed tracing system * How to get the most value out of end-to-end tracing * Learn about open standards in the space * Learn about code instrumentation and operating a tracing infrastructure * Learn where distributed tracing fits into microservices as a core function Who this book is for Any developer interested in testing large systems will find this book very revealing and in places, surprising. Every microservice architect and developer should have an insight into distributed tracing, and the book will help them on their way. System administrators with some development skills will also benefit. No particular programming language skills are required, although an ability to read Java, while non-essential, will help with the core chapters.

A comprehensive guide to mastering the most advanced Hadoop 3 concepts Key Features * Get to grips with the newly introduced features and capabilities of Hadoop 3 * Crunch and process data using MapReduce, YARN, and a host of tools within the Hadoop ecosystem * Sharpen your Hadoop skills with real-world case studies and code Book Description Apache Hadoop is one of the most popular big data solutions for distributed storage and for processing large chunks of data. With Hadoop 3, Apache promises to provide a high-performance, more fault-tolerant, and highly efficient big data processing platform, with a focus on improved scalability and increased efficiency. With this guide, you’ll understand advanced concepts of the Hadoop ecosystem tool. You’ll learn how Hadoop works internally, study advanced concepts of different ecosystem tools, discover solutions to real-world use cases, and understand how to secure your cluster. It will then walk you through HDFS, YARN, MapReduce, and Hadoop 3 concepts. You’ll be able to address common challenges like using Kafka efficiently, designing low latency, reliable message delivery Kafka systems, and handling high data volumes. As you advance, you’ll discover how to address major challenges when building an enterprise-grade messaging system, and how to use different stream processing systems along with Kafka to fulfil your enterprise goals. By the end of this book, you’ll have a complete understanding of how components in the Hadoop ecosystem are effectively integrated to implement a fast and reliable data pipeline, and you’ll be equipped to tackle a range of real-world problems in data pipelines. What you will learn * Gain an in-depth understanding of distributed computing using Hadoop 3 * Develop enterprise-grade applications using Apache Spark, Flink, and more * Build scalable and high-performance Hadoop data pipelines with security, monitoring, and data governance * Explore batch data processing patterns and how to model data in Hadoop * Master best practices for enterprises using, or planning to use, Hadoop 3 as a data platform * Understand security aspects of Hadoop, including authorization and authentication Who this book is for If you want to become a big data professional by mastering the advanced concepts of Hadoop, this book is for you. You’ll also find this book useful if you’re a Hadoop professional looking to strengthen your knowledge of the Hadoop ecosystem. Fundamental knowledge of the Java programming language and basics of Hadoop is necessary to get started with this book.

This volume represents the combination of two special issues of the Journal of Consciousness Studies on the topic of the technological singularity. Could artificial intelligence really out-think us, and what would be the likely repercussions if it could? Leading authors contribute to the debate, which takes the form of a target chapter by philosopher David Chalmers, plus commentaries from the likes of Daniel Dennett, Nick Bostrom, Ray Kurzweil, Ben Goertzel, Frank Tipler, among many others. Chalmers then responds to the commentators to round off the discussion.

Implement defensive techniques in your ecosystem successfully with Python Key Features * Identify and expose vulnerabilities in your infrastructure with Python * Learn custom exploit development . * Make robust and powerful cybersecurity tools with Python Book Description With the current technological and infrastructural shift, penetration testing is no longer a process-oriented activity. Modern-day penetration testing demands lots of automation and innovation; the only language that dominates all its peers is Python. Given the huge number of tools written in Python, and its popularity in the penetration testing space, this language has always been the first choice for penetration testers. Hands-On Penetration Testing with Python walks you through advanced Python programming constructs. Once you are familiar with the core concepts, you’ll explore the advanced uses of Python in the domain of penetration testing and optimization. You’ll then move on to understanding how Python, data science, and the cybersecurity ecosystem communicate with one another. In the concluding chapters, you’ll study exploit development, reverse engineering, and cybersecurity use cases that can be automated with Python. By the end of this book, you’ll have acquired adequate skills to leverage Python as a helpful tool to pentest and secure infrastructure, while also creating your own custom exploits. What you will learn * Get to grips with Custom vulnerability scanner development * Familiarize yourself with web application scanning automation and exploit development * Walk through day-to-day cybersecurity scenarios that can be automated with Python * Discover enterprise-or organization-specific use cases and threat-hunting automation * Understand reverse engineering, fuzzing, buffer overflows , key-logger development, and exploit development for buffer overflows. * Understand web scraping in Python and use it for processing web responses * Explore Security Operations Centre (SOC) use cases * Get to understand Data Science, Python, and cybersecurity all under one hood Who this book is for If you are a security consultant , developer or a cyber security enthusiast with little or no knowledge of Python and want in-depth insight into how the pen-testing ecosystem and python combine to create offensive tools , exploits , automate cyber security use-cases and much more then this book is for you. Hands-On Penetration Testing with Python guides you through the advanced uses of Python for cybersecurity and pen-testing, helping you to better understand security loopholes within your infrastructure .

Illusionism is the view that phenomenal consciousness (in the philosophers' sense) is an illusion. This book is a reprint of a special issue of the Journal of Consciousness Studies devoted to this topic. It takes the form of a target paper by the editor, followed by commentaries from various thinkers, including leading defenders of the theory such as Daniel Dennett, Nicholas Humphrey, Derk Pereboom and Georges Rey. A number of disciplines are represented and different viewpoints are discussed and defended. The colleciton is tied together with a response to the commentaries from the editor.

Power up your network applications with Python programming Key Features * Master Python skills to develop powerful network applications * Grasp the fundamentals and functionalities of SDN * Design multi-threaded, event-driven architectures for echo and chat servers Book Description This Learning Path highlights major aspects of Python network programming such as writing simple networking clients, creating and deploying SDN and NFV systems, and extending your network with Mininet. You’ll also learn how to automate legacy and the latest network devices. As you progress through the chapters, you’ll use Python for DevOps and open source tools to test, secure, and analyze your network. Toward the end, you'll develop client-side applications, such as web API clients, email clients, SSH, and FTP, using socket programming. By the end of this Learning Path, you will have learned how to analyze a network's security vulnerabilities using advanced network packet capture and analysis techniques. This Learning Path includes content from the following Packt products: * Practical Network Automation by Abhishek Ratan * Mastering Python Networking by Eric Chou * Python Network Programming Cookbook, Second Edition by Pradeeban Kathiravelu, Dr. M. O. Faruque Sarker What you will learn * Create socket-based networks with asynchronous models * Develop client apps for web APIs, including S3 Amazon and Twitter * Talk to email and remote network servers with different protocols * Integrate Python with Cisco, Juniper, and Arista eAPI for automation * Use Telnet and SSH connections for remote system monitoring * Interact with websites via XML-RPC, SOAP, and REST APIs * Build networks with Ryu, OpenDaylight, Floodlight, ONOS, and POX * Configure virtual networks in different deployment environments Who this book is for If you are a Python developer or a system administrator who wants to start network programming, this Learning Path gets you a step closer to your goal. IT professionals and DevOps engineers who are new to managing network devices or those with minimal experience looking to expand their knowledge and skills in Python will also find this Learning Path useful. Although prior knowledge of networking is not required, some experience in Python programming will be helpful for a better understanding of the concepts in the Learning Path.

At first glance, issues like economic inequality, healthcare, climate change, and abortion seem unrelated. However, when thinking and talking about them, people reliably fall into two camps: conservative and liberal. What explains this divide? Why do conservatives and liberals hold the positions they do? And what is the conceptual nature of those who decide elections, commonly called the "e;political middle"e;?The answers are profound. They have to do with how our minds and brains work. Political attitudes are the product of what cognitive scientists call Embodied Cognition - the grounding of abstract thought in everyday world experience. Clashing beliefs about how to run nations largely arise from conflicting beliefs about family life: conservatives endorse a strict father and liberals a nurturant parent model. So-called "e;middle"e; voters are not in the middle at all. They are morally biconceptual, divided between both models, and as a result highly susceptible to moral political persuasion.In this brief introduction, Lakoff and Wehling reveal how cognitive science research has advanced our understanding of political thought and language, forcing us to revise common folk theories about the rational voter.

Big data processing and analytics at speed and scale using command line tools. Key Features * Perform string processing, numerical computations, and more using CLI tools * Understand the essential components of data science development workflow * Automate data pipeline scripts and visualization with the command line Book Description The Command Line has been in existence on UNIX-based OSes in the form of Bash shell for over 3 decades. However, very little is known to developers as to how command-line tools can be OSEMN (pronounced as awesome and standing for Obtaining, Scrubbing, Exploring, Modeling, and iNterpreting data) for carrying out simple-to-advanced data science tasks at speed. This book will start with the requisite concepts and installation steps for carrying out data science tasks using the command line. You will learn to create a data pipeline to solve the problem of working with small-to medium-sized files on a single machine. You will understand the power of the command line, learn how to edit files using a text-based and an. You will not only learn how to automate jobs and scripts, but also learn how to visualize data using the command line. By the end of this book, you will learn how to speed up the process and perform automated tasks using command-line tools. What you will learn * Understand how to set up the command line for data science * Use AWK programming language commands to search quickly in large datasets. * Work with files and APIs using the command line * Share and collect data with CLI tools * Perform visualization with commands and functions * Uncover machine-level programming practices with a modern approach to data science Who this book is for This book is for data scientists and data analysts with little to no knowledge of the command line but has an understanding of data science. Perform everyday data science tasks using the power of command line tools.

Implement machine learning and deep learning methodologies to build smart, cognitive AI projects using Python Key Features * A go-to guide to help you master AI algorithms and concepts * 8 real-world projects tackling different challenges in healthcare, e-commerce, and surveillance * Use TensorFlow, Keras, and other Python libraries to implement smart AI applications Book Description This book will be a perfect companion if you want to build insightful projects from leading AI domains using Python. The book covers detailed implementation of projects from all the core disciplines of AI. We start by covering the basics of how to create smart systems using machine learning and deep learning techniques. You will assimilate various neural network architectures such as CNN, RNN, LSTM, to solve critical new world challenges. You will learn to train a model to detect diabetic retinopathy conditions in the human eye and create an intelligent system for performing a video-to-text translation. You will use the transfer learning technique in the healthcare domain and implement style transfer using GANs. Later you will learn to build AI-based recommendation systems, a mobile app for sentiment analysis and a powerful chatbot for carrying customer services. You will implement AI techniques in the cybersecurity domain to generate Captchas. Later you will train and build autonomous vehicles to self-drive using reinforcement learning. You will be using libraries from the Python ecosystem such as TensorFlow, Keras and more to bring the core aspects of machine learning, deep learning, and AI. By the end of this book, you will be skilled to build your own smart models for tackling any kind of AI problems without any hassle. What you will learn * Build an intelligent machine translation system using seq-2-seq neural translation machines * Create AI applications using GAN and deploy smart mobile apps using TensorFlow * Translate videos into text using CNN and RNN * Implement smart AI Chatbots, and integrate and extend them in several domains * Create smart reinforcement, learning-based applications using Q-Learning * Break and generate CAPTCHA using Deep Learning and Adversarial Learning Who this book is for This book is intended for data scientists, machine learning professionals, and deep learning practitioners who are ready to extend their knowledge and potential in AI. If you want to build real-life smart systems to play a crucial role in every complex domain, then this book is what you need. Knowledge of Python programming and a familiarity with basic machine learning and deep learning concepts are expected to help you get the most out of the book

Are you a fan of rugby league? Do you play the game yourself or enjoy watching others who do? Do you know the history of this fast paced contact sport? If you think you know all about rugby league you are certain to want to test yourself with the 250 challenging questions in this new quiz book. Find out about the origins of the game, the all-time great players and the part they played in rugby league history, famous stadiums, cup competitions, winners and losers, as well as all those memorable moments from over one hundred years of rugby league. The Rugby League Quiz Book will tell you everything you ever wanted to know about the game past and present. Full of facts and figures, this book will appeal to rugby league fans of all ages and is a great way for younger players to learn more about the history of the sport. A real treasure trove of information and a must-have book for rugby aficionados of all ages.

Are you a fan of horse racing? Do follow all the big races and enjoy the occasional bet? Can you name the great jockeys through the years and the events they have won? If you answered yes to any of the above, or would like to find out more about professional horse racing, you won't want to be without the new Horse Racing Quiz Book. Which two fences are only jumped once in the Grand National? Part of which UK racecourse is within a famous area known as the Knavesmire? What are the Christian names of the Hills twins, both Classic winning jockeys? The answers to these and many similar questions can all be found in this book.The 250 questions, some easy, some more challenging, will quickly uncover how much you know about the fast-paced world of horse racing. Covering all the big races, famous jockeys, racecourses, horses, owners and trainers as well as the history of horse racing, this is a must-have for anyone interested in this action-packed sport.

Your hands-on reference guide to developing, training, and optimizing your machine learning models Key Features * Your guide to learning efficient machine learning processes from scratch * Explore expert techniques and hacks for a variety of machine learning concepts * Write effective code in R, Python, Scala, and Spark to solve all your machine learning problems Book Description Machine learning makes it possible to learn about the unknowns and gain hidden insights into your datasets by mastering many tools and techniques. This book guides you to do just that in a very compact manner. After giving a quick overview of what machine learning is all about, Machine Learning Quick Reference jumps right into its core algorithms and demonstrates how they can be applied to real-world scenarios. From model evaluation to optimizing their performance, this book will introduce you to the best practices in machine learning. Furthermore, you will also look at the more advanced aspects such as training neural networks and work with different kinds of data, such as text, time-series, and sequential data. Advanced methods and techniques such as causal inference, deep Gaussian processes, and more are also covered. By the end of this book, you will be able to train fast, accurate machine learning models at your fingertips, which you can easily use as a point of reference. What you will learn * Get a quick rundown of model selection, statistical modeling, and cross-validation * Choose the best machine learning algorithm to solve your problem * Explore kernel learning, neural networks, and time-series analysis * Train deep learning models and optimize them for maximum performance * Briefly cover Bayesian techniques and sentiment analysis in your NLP solution * Implement probabilistic graphical models and causal inferences * Measure and optimize the performance of your machine learning models Who this book is for If you’re a machine learning practitioner, data scientist, machine learning developer, or engineer, this book will serve as a reference point in building machine learning solutions. You will also find this book useful if you’re an intermediate machine learning developer or data scientist looking for a quick, handy reference to all the concepts of machine learning. You’ll need some exposure to machine learning to get the best out of this book.

Perform advanced dashboard, visualization, and analytical techniques with Tableau Desktop, Tableau Prep, and Tableau Server Key Features * Unique problem-solution approach to aid effective business decision-making * Create interactive dashboards and implement powerful business intelligence solutions * Includes best practices on using Tableau with modern cloud analytics services Book Description Tableau has been one of the most popular business intelligence solutions in recent times, thanks to its powerful and interactive data visualization capabilities. Tableau 2019.x Cookbook is full of useful recipes from industry experts, who will help you master Tableau skills and learn each aspect of Tableau's ecosystem. This book is enriched with features such as Tableau extracts, Tableau advanced calculations, geospatial analysis, and building dashboards. It will guide you with exciting data manipulation, storytelling, advanced filtering, expert visualization, and forecasting techniques using real-world examples. From basic functionalities of Tableau to complex deployment on Linux, you will cover it all. Moreover, you will learn advanced features of Tableau using R, Python, and various APIs. You will learn how to prepare data for analysis using the latest Tableau Prep. In the concluding chapters, you will learn how Tableau fits the modern world of analytics and works with modern data platforms such as Snowflake and Redshift. In addition, you will learn about the best practices of integrating Tableau with ETL using Matillion ETL. By the end of the book, you will be ready to tackle business intelligence challenges using Tableau's features. What you will learn * Understand the basic and advanced skills of Tableau Desktop * Implement best practices of visualization, dashboard, and storytelling * Learn advanced analytics with the use of build in statistics * Deploy the multi-node server on Linux and Windows * Use Tableau with big data sources such as Hadoop, Athena, and Spectrum * Cover Tableau built-in functions for forecasting using R packages * Combine, shape, and clean data for analysis using Tableau Prep * Extend Tableau’s functionalities with REST API and R/Python Who this book is for Tableau 2019.x Cookbook is for data analysts, data engineers, BI developers, and users who are looking for quick solutions to common and not-so-common problems faced while using Tableau products. Put each recipe into practice by bringing the latest offerings of Tableau 2019.x to solve real-world analytics and business intelligence challenges. Some understanding of BI concepts and Tableau is required.