Master the intricacies of Tableau to create effective data visualizations About This Book Arm yourself with an arsenal of advanced chart types and geocoding to efficiently and engagingly present information Map a grid over a network node diagram and use that grid to demonstrate loads, processing time, and more in Tableau Integrate R with Tableau by utilizing R functions, libraries, and saved models Who This Book Is For If you are a business analyst without developer-level programming skills, then this book is for you. You are expected to have at least a fundamental understanding of Tableau and basic knowledge of joins, however SQL knowledge is not assumed. You should have basic computer skills, including at least moderate Excel proficiency. What You Will Learn Create a worksheet that can display the current balance for any given period in time Recreate a star schema from in a data warehouse in Tableau Combine level of detail calculations with table calculations, sets, and parameters Create custom polygons to build filled maps for area codes in the USA Visualize data using a set of analytical and advanced charting techniques Know when to use Tableau instead of PowerPoint Build a dashboard and export it to PowerPoint In Detail Tableau has emerged as one of the most popular Business Intelligence solutions in recent times, thanks to its powerful and interactive data visualization capabilities. This book will empower you to become a master in Tableau by exploiting the many new features introduced in Tableau 10.0. You will embark on this exciting journey by getting to know the valuable methods of utilizing advanced calculations to solve complex problems. These techniques include creative use of different types of calculations such as row-level, aggregate-level, and more. You will discover how almost any data visualization challenge can be met in Tableau by getting a proper understanding of the tool’s inner workings and creatively exploring possibilities. You’ll be armed with an arsenal of advanced chart types and techniques to enable you to efficiently and engagingly present information to a variety of audiences through the use of clear, efficient, and engaging dashboards. Explanations and examples of efficient and inefficient visualization techniques, well-designed and poorly designed dashboards, and compromise options when Tableau consumers will not embrace data visualization will build on your understanding of Tableau and how to use it efficiently. By the end of the book, you will be equipped with all the information you need to create effective dashboards and data visualization solutions using Tableau. Style and approach This book takes a direct approach, to systematically evolve to more involved functionalities such as advanced calculation, parameters & sets, data blending and R integration. This book will help you gain skill in building visualizations previously beyond your capacity.

Learn to get the most out of your business data to optimize your business About This Book This book will enable and empower you to break free of the shackles of spreadsheets Learn to make informed decisions using the data at hand with this highly practical, comprehensive guide This book includes real-world use cases that teach you how analytics can be put to work to optimize your business Using a fictional transactional dataset in raw form, you’ll work your way up to ultimately creating a fully-functional warehouse and a fleshed-out BI platform Who This Book Is For This book is for anyone who has wrangled with data to try to perform automated data analysis through visualizations for themselves or their customers. This highly-customized guide is for developers who know a bit about analytics but don't know how to make use of it in the field of business intelligence. What You Will Learn Create a BI environment that enables self-service reporting Understand SQL and the aggregation of data Develop a data model suitable for analytical reporting Connect a data warehouse to the analytic reporting tools Understand the specific benefits behind visualizations with D3.js, R, Tableau, QlikView, and Python Get to know the best practices to develop various reports and applications when using BI tools Explore the field of data analysis with all the data we will use for reporting In Detail Business Intelligence (BI) is at the crux of revolutionizing enterprise. Everyone wants to minimize losses and maximize profits. Thanks to Big Data and improved methodologies to analyze data, Data Analysts and Data Scientists are increasingly using data to make informed decisions. Just knowing how to analyze data is not enough, you need to start thinking how to use data as a business asset and then perform the right analysis to build an insightful BI solution. Efficient BI strives to achieve the automation of data for ease of reporting and analysis. Through this book, you will develop the ability to think along the right lines and use more than one tool to perform analysis depending on the needs of your business. We start off by preparing you for data analytics. We then move on to teach you a range of techniques to fetch important information from various databases, which can be used to optimize your business. The book aims to provide a full end-to-end solution for an environment setup that can help you make informed business decisions and deliver efficient and automated BI solutions to any company. It is a complete guide for implementing Business intelligence with the help of the most powerful tools like D3.js, R, Tableau, Qlikview and Python that are available on the market. Style and approach Packed with real-world examples, this pragmatic guide helps you polish your data and make informed decisions for your business. We cover both business and data analysis perspectives, blending theory and practical hands-on work so that you perceive data as a business asset.

Over 60 practical recipes on data exploration and analysis About This Book Clean dirty data, extract accurate information, and explore the relationships between variables Forecast the output of an electric plant and the water flow of American rivers using pandas, NumPy, Statsmodels, and scikit-learn Find and extract the most important features from your dataset using the most efficient Python libraries Who This Book Is For If you are a beginner or intermediate-level professional who is looking to solve your day-to-day, analytical problems with Python, this book is for you. Even with no prior programming and data analytics experience, you will be able to finish each recipe and learn while doing so. What You Will Learn Read, clean, transform, and store your data usng Pandas and OpenRefine Understand your data and explore the relationships between variables using Pandas and D3.js Explore a variety of techniques to classify and cluster outbound marketing campaign calls data of a bank using Pandas, mlpy, NumPy, and Statsmodels Reduce the dimensionality of your dataset and extract the most important features with pandas, NumPy, and mlpy Predict the output of a power plant with regression models and forecast water flow of American rivers with time series methods using pandas, NumPy, Statsmodels, and scikit-learn Explore social interactions and identify fraudulent activities with graph theory concepts using NetworkX and Gephi Scrape Internet web pages using urlib and BeautifulSoup and get to know natural language processing techniques to classify movies ratings using NLTK Study simulation techniques in an example of a gas station with agent-based modeling In Detail Data analysis is the process of systematically applying statistical and logical techniques to describe and illustrate, condense and recap, and evaluate data. Its importance has been most visible in the sector of information and communication technologies. It is an employee asset in almost all economy sectors. This book provides a rich set of independent recipes that dive into the world of data analytics and modeling using a variety of approaches, tools, and algorithms. You will learn the basics of data handling and modeling, and will build your skills gradually toward more advanced topics such as simulations, raw text processing, social interactions analysis, and more. First, you will learn some easy-to-follow practical techniques on how to read, write, clean, reformat, explore, and understand your data—arguably the most time-consuming (and the most important) tasks for any data scientist. In the second section, different independent recipes delve into intermediate topics such as classification, clustering, predicting, and more. With the help of these easy-to-follow recipes, you will also learn techniques that can easily be expanded to solve other real-life problems such as building recommendation engines or predictive models. In the third section, you will explore more advanced topics: from the field of graph theory through natural language processing, discrete choice modeling to simulations. You will also get to expand your knowledge on identifying fraud origin with the help of a graph, scrape Internet websites, and classify movies based on their reviews. By the end of this book, you will be able to efficiently use the vast array of tools that the Python environment has to offer. Style and approach This hands-on recipe guide is divided into three sections that tackle and overcome real-world data modeling problems faced by data analysts/scientist in their everyday work. Each independent recipe is written in an easy-to-follow and step-by-step fashion.

Build effective applications by applying Odoo development best practices About This Book Each recipe stands by itself as much as possible, so that you can jump straight into the topics you prefer The recipes included cover all the major development areas of Odoo and the most important techniques explained through real-life projects From seasoned authors, learn the tricks of becoming a productive developer with the Odoo framework Who This Book Is For If you are a Python developer who wants to learn or consolidate your Odoo development skills, then this book is for you! Some experience with the JavaScript programming language and web development is required to fully benefit from the front-end chapters. What You Will Learn Install and manage Odoo environments and instances Use Models to define your application's data structures Add business logic to your applications Implement automated tests and debug Odoo apps Use back-end views to create a user interface Get to know about the access security model and internationalization features Develop front-end website features Extend the web client with new widgets and features In Detail Odoo is a full-featured open source ERP with a focus on extensibility. The flexibility and sustainability of open source is also a key selling point of Odoo. It is built on a powerful framework for rapid application development, both for back-end applications and front-end websites. The book starts by covering Odoo installation and administration, and provides a gentle introduction to application development. It then dives deep into several of the areas that an experienced developer will need to use. You’ll learn implement business logic, adapt the UI, and extend existing features. Style and Approach These practical and easy-to-follow recipes are presented step-by-step, with dozens of hands-on recipes to boost your Odoo skills. This book can also be used as a reference guide for your daily work.

Attain expert-level proficiency with Git for enhanced productivity and efficient collaboration by mastering advanced distributed version control features About This Book Set up Git for solo and collaborative development Harness the full power of Git version control system to customize Git behavior, manipulate history, integrate external tools and explore platform shortcuts A detailed guide, which explains how to apply advanced Git techniques and workflows and ways to handle submodules Who This Book Is For If you are a Git user with reasonable knowledge of Git and familiarity with basic concepts such as branching, merging, staging, and workflows, this is the book for you. Basic knowledge of installing Git and software configuration management concepts is essential. What You Will Learn Explore project history, find revisions using different criteria, and filter and format how history looks Manage your working directory and staging area for commits and interactively create new revisions and amend them Set up repositories and branches for collaboration Submit your own contributions and integrate contributions from other developers via merging or rebasing Customize Git behavior system-wide, on a per-user, per-repository, and per-file basis Take up the administration and set up of Git repositories, configure access, find and recover from repository errors, and perform repository maintenance Chose a workflow and configure and set up support for the chosen workflow In Detail Git is one of the most popular types of Source Code Management (SCM) and Distributed Version Control System (DVCS). Despite the powerful and versatile nature of the tool enveloping strong support for nonlinear development and the ability to handle large projects efficiently, it is a complex tool and often regarded as “user-unfriendly”. Getting to know the ideas and concepts behind the architecture of Git will help you make full use of its power and understand its behavior. Learning the best practices and recommended workflows should help you to avoid problems and ensure trouble-free development. The book scope is meticulously designed to help you gain deeper insights into Git's architecture, its underlying concepts, behavior, and best practices. Mastering Git starts with a quick implementation example of using Git for a collaborative development of a sample project to establish the foundation knowledge of Git operational tasks and concepts. Furthermore, as you progress through the book, the tutorials provide detailed de*ions of various areas of usage: from archaeology, through managing your own work, to working with other developers. This book also helps augment your understanding to examine and explore project history, create and manage your contributions, set up repositories and branches for collaboration in centralized and distributed version control, integrate work from other developers, customize and extend Git, and recover from repository errors. By exploring advanced Git practices, you will attain a deeper understanding of Git’s behavior, allowing you to customize and extend existing recipes and write your own. Style and approach Step-by-step instructions and useful information make this book the ultimate guide to understanding and mastering Git. This book will show road to mastery example by example, while explaining mental model of Git. The Introduction section covers the 'Essentials' just for refreshing the basics. The main highlight is that the concepts are based on HOW the technology/framework works and not just practical 'WHAT to do'.

Over 70 recipes to get you writing powerful and efficient multithreaded, asynchronous, and parallel programs in C# 6.0 About This Book Rewritten and updated to take advantage of the latest C# 6 features Learn about multithreaded, asynchronous, and parallel programming through hands-on, code-first examples Use these recipes to build fast, scalable, and reliable applications in C# Who This Book Is For This book is aimed at those who are new to multithreaded programming, and who are looking for a quick and easy way to get started. It is assumed that you have some experience in C# and .NET already, and you should also be familiar with basic computer science terminology and basic algorithms and data structures. What You Will Learn Use C# 6.0 asynchronous language features Work with raw threads, synchronize threads, and coordinate their work Develop your own asynchronous API with Task Parallel Library Work effectively with a thread pool Scale up your server application with I/O threads Parallelize your LINQ queries with PLINQ Use common concurrent collections Apply different parallel programming patterns Use Reactive Extensions to run asynchronous operations and manage their options In Detail Multi-core processors are synonymous with computing speed and power in today’s world, which is why multithreading has become a key concern for C# developers. Multithreaded code helps you create effective, scalable, and responsive applications. This is an easy-to-follow guide that will show you difficult programming problems in context. You will learn how to solve them with practical, hands-on, recipes. With these recipes, you’ll be able to start creating your own scalable and reliable multithreaded applications. Starting from learning what a thread is, we guide you through the basics and then move on to more advanced concepts such as task parallel libraries, C# asynchronous functions, and much more. Rewritten to the latest C# specification, C# 6, and updated with new and modern recipes to help you make the most of the hardware you have available, this book will help you push the boundaries of what you thought possible in C#. Style and approach This is an easy-to-follow guide full of hands-on examples of real-world multithreading tasks. Each topic is explained and placed in context, and for the more inquisitive, there are also more in-depth details of the concepts used.

Master the intricacies of Elasticsearch 5 and use it to create flexible and scalable search solutions About This Book Master the searching, indexing, and aggregation features in ElasticSearch Improve users’ search experience with Elasticsearch’s functionalities and develop your own Elasticsearch plugins A comprehensive, step-by-step guide to master the intricacies of ElasticSearch with ease Who This Book Is For If you have some prior working experience with Elasticsearch and want to take your knowledge to the next level, this book will be the perfect resource for you.If you are a developer who wants to implement scalable search solutions with Elasticsearch, this book will also help you. Some basic knowledge of the query DSL and data indexing is required to make the best use of this book. What You Will Learn Understand Apache Lucene and Elasticsearch 5’s design and architecture Use and configure the new and improved default text scoring mechanism in Apache Lucene 6 Know how to overcome the pitfalls while handling relational data in Elasticsearch Learn about choosing the right queries according to the use cases and master the *ing module including new default *ing language, painlessly Explore the right way of scaling production clusters to improve the performance of Elasticsearch Master the searching, indexing, and aggregation features in Elasticsearch Develop your own Elasticsearch plugins to extend the functionalities of Elasticsearch In Detail Elasticsearch is a modern, fast, distributed, scalable, fault tolerant, and open source search and analytics engine. Elasticsearch leverages the capabilities of Apache Lucene, and provides a new level of control over how you can index and search even huge sets of data. This book will give you a brief recap of the basics and also introduce you to the new features of Elasticsearch 5. We will guide you through the intermediate and advanced functionalities of Elasticsearch, such as querying, indexing, searching, and modifying data. We’ll also explore advanced concepts, including aggregation, index control, sharding, replication, and clustering. We’ll show you the modules of monitoring and administration available in Elasticsearch, and will also cover backup and recovery. You will get an understanding of how you can scale your Elasticsearch cluster to contextualize it and improve its performance. We’ll also show you how you can create your own analysis plugin in Elasticsearch. By the end of the book, you will have all the knowledge necessary to master Elasticsearch and put it to efficient use. Style and approach This comprehensive guide covers intermediate and advanced concepts in Elasticsearch as well as their implementation. An easy-to-follow approach means you’ll be able to master even advanced querying, searching, and administration tasks with ease.

Learn idiomatic, efficient, clean, and extensible Go design and concurrency patterns by using TDD About This Book A highly practical guide filled with numerous examples unleashing the power of design patterns with Go. Discover an introduction of the CSP concurrency model by explaining GoRoutines and channels. Get a full explanation, including comprehensive text and examples, of all known GoF design patterns in Go. Who This Book Is For The target audience is both beginner- and advanced-level developers in the Go programming language. No knowledge of design patterns is expected. What You Will Learn All basic syntax and tools needed to start coding in Go Encapsulate the creation of complex objects in an idiomatic way in Go Create unique instances that cannot be duplicated within a program Understand the importance of object encapsulation to provide clarity and maintainability Prepare cost-effective actions so that different parts of the program aren’t affected by expensive tasks Deal with channels and GoRoutines within the Go context to build concurrent application in Go in an idiomatic way In Detail Go is a multi-paradigm programming language that has built-in facilities to create concurrent applications. Design patterns allow developers to efficiently address common problems faced during developing applications. Go Design Patterns will provide readers with a reference point to software design patterns and CSP concurrency design patterns to help them build applications in a more idiomatic, robust, and convenient way in Go. The book starts with a brief introduction to Go programming essentials and quickly moves on to explain the idea behind the creation of design patterns and how they appeared in the 90’s as a common "language" between developers to solve common tasks in object-oriented programming languages. You will then learn how to apply the 23 Gang of Four (GoF) design patterns in Go and also learn about CSP concurrency patterns, the "killer feature" in Go that has helped Google develop software to maintain thousands of servers. With all of this the book will enable you to understand and apply design patterns in an idiomatic way that will produce concise, readable, and maintainable software. Style and approach This book will teach widely used design patterns and best practices with Go in a step-by-step manner. The code will have detailed examples, to allow programmers to apply design patterns in their day-to-day coding.

Get acquainted with the world of LXC About This Book Get the most practical and up-to-date resource on LXC and take full advantage of what Linux containers can offer in the day-to-day operations of large-scale applications Learn how to deploy and administer various workloads such as web applications inside LXC Save your organization time and money by building robust and secure containers and by speeding the deployment process of your software Who This Book Is For This book is for Linux engineers and software developers who are looking to deploy applications in a fast, secure, and scalable way for use in testing and production. What You Will Learn Deep dive into the foundations of Linux containers with kernel namespaces and cgroups Install, configure, and administer Linux containers with LXC and libvirt Begin writing applications using Python libvirt bindings Take an in-depth look at container networking Set up monitoring and security with LXC Build and deploy a highly available application with LXC in the cloud In Detail In recent years, containers have gained wide adoption by businesses running a variety of application loads. This became possible largely due to the advent of kernel namespaces and better resource management with control groups (cgroups). Linux containers (LXC) are a direct implementation of those kernel features that provide operating system level virtualization without the overhead of a hypervisor layer. This book starts by introducing the foundational concepts behind the implementation of LXC, then moves into the practical aspects of installing and configuring LXC containers. Moving on, you will explore container networking, security, and backups. You will also learn how to deploy LXC with technologies like Open Stack and Vagrant. By the end of the book, you will have a solid grasp of how LXC is implemented and how to run production applications in a highly available and scalable way. Style and approach A practical guide that introduces the core technologies behind Linux containers and provides a deep dive into installation, configuration, and operations of LXC.

Over 90 practical, actionable recipes to automate, test, and manage your infrastructure quickly and effectively About This Book Bring down your delivery timeline from days to hours by treating your server configurations and VMs as code, just like you would with software code. Take your existing knowledge and skill set with your existing tools (Puppet, Chef, or Docker) to the next level and solve IT infrastructure challenges. Use practical recipes to use code to provision and deploy servers and applications and have greater control of your infrastructure. Who This Book Is For This book is for DevOps engineers and developers working in cross-functional teams or operations and would now switch to IAC to manage complex infrastructures. What You Will Learn Provision local and remote development environments with Vagrant Automate production infrastructures with Terraform, Ansible and Cloud-init on AWS, OpenStack, Google Cloud, Digital Ocean, and more Manage and test automated systems using Chef and Puppet Build, ship, and debug optimized Docker containers Explore the best practices to automate and test everything from cloud infrastructures to operating system configuration In Detail Infrastructure as Code (IAC) is a key aspect of the DevOps movement, and this book will show you how to transform the way you work with your infrastructure—by treating it as software. This book is dedicated to helping you discover the essentials of infrastructure automation and its related practices; the over 90 organized practical solutions will demonstrate how to work with some of the very best tools and cloud solutions. You will learn how to deploy repeatable infrastructures and services on AWS, OpenStack, Google Cloud, and Digital Ocean. You will see both Ansible and Terraform in action, manipulate the best bits from cloud-init to easily bootstrap instances, and simulate consistent environments locally or remotely using Vagrant. You will discover how to automate and test a range of system tasks using Chef or Puppet. You will also build, test, and debug various Docker containers having developers’ interests in mind. This book will help you to use the right tools, techniques, and approaches to deliver working solutions for today’s modern infrastructure challenges. Style and approach This is a recipe-based book that allows you to venture into some of the most cutting-edge practices and techniques about IAC and solve immediate problems when trying to implement them.

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

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

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

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

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

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

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

Spatial statistics has the potential to provide insight that is not otherwise available through traditional GIS tools. This book is designed to introduce you to the use of spatial statistics so you can solve complex geographic analysis. The book begins by introducing you to the many spatial statistics tools available in ArcGIS. You will learn how to analyze patterns, map clusters, and model spatial relationships with these tools. Further on, you will explore how to extend the spatial statistics tools currently available in ArcGIS, and use the R programming language to create custom tools in ArcGIS through the ArcGIS Bridge using real-world examples. At the end of the book, you will be presented with two exciting case studies where you will be able to practically apply all your learning to analyze and gain insights into real estate data. What you will learn ?Get to know how to measure geographic distributions ?Perform clustering analysis including hot spot and outlier analysis ?Conduct data conversion tasks using the Utilities toolset ?Understand how to use the tools provided by the Mapping Clusters toolset in the Spatial Statistics Toolbox ?Get to grips with the basics of R for performing spatial statistical programming ?Create custom ArcGIS tools with R and ArcGIS Bridge ?Understand the application of Spatial Statistics tools

Java is the most popular programming language, according to the TIOBE index, and it is a typical choice for running production systems in many companies, both in the startup world and among large enterprises. Not surprisingly, it is also a common choice for creating data science applications: it is fast and has a great set of data processing tools, both built-in and external. What is more, choosing Java for data science allows you to easily integrate solutions with existing software, and bring data science into production with less effort. This book will teach you how to create data science applications with Java. First, we will revise the most important things when starting a data science application, and then brush up the basics of Java and machine learning before diving into more advanced topics. We start by going over the existing libraries for data processing and libraries with machine learning algorithms. After that, we cover topics such as classification and regression, dimensionality reduction and clustering, information retrieval and natural language processing, and deep learning and big data. Finally, we finish the book by talking about the ways to deploy the model and evaluate it in production settings. What you will learn ?Get a solid understanding of the data processing toolbox available in Java ?Explore the data science ecosystem available in Java

Work through recipes to unlock the full potential of the next generation graphics API―Vulkan About This Book ?This book explores a wide range of modern graphics programming techniques and GPU compute methods to make the best use of the Vulkan API ?Learn techniques that can be applied to a wide range of platforms desktop, smartphones, and embedded devices Who This Book Is For This book is ideal for developers who know C/C++ languages, have some basic familiarity with graphics programming, and now want to take advantage of the new Vulkan API in the process of building next generation computer graphics. Some basic familiarity of Vulkan would be useful to follow the recipes. OpenGL developers who want to take advantage of the Vulkan API will also find this book useful. What You Will Learn?Work with Swapchain to present images on screen ?Create, submit, and synchronize operations processed by the hardware ?Create buffers and images, manage their memory, and upload data to them from CPU ?Explore de*or sets and set up an interface between application and shaders ?Organize drawing operations into a set of render passes and subpasses ?Prepare graphics pipelines to draw 3D scenes and compute pipelines to perform mathematical calculations ?Implement geometry projection and tessellation, texturing, lighting, and post-processing techniques ?Write shaders in GLSL and convert them into SPIR-V assemblies ?Find out about and

Achieve improved network programmability and automation by leveraging powerful network programming concepts, algorithms, and tools Key Features * Deal with remote network servers using SSH, FTP, SNMP and LDAP protocols. * Design multi threaded and event-driven architectures for asynchronous servers programming. * Leverage your Python programming skills to build powerful network applications Book Description Network programming has always been a demanding task. With full-featured and well-documented libraries all the way up the stack, Python makes network programming the enjoyable experience it should be. Starting with a walk through of today's major networking protocols, through this book, you'll learn how to employ Python for network programming, how to request and retrieve web resources, and how to extract data in major formats over the web. You will utilize Python for emailing using different protocols, and you'll interact with remote systems and IP and DNS networking. You will cover the connection of networking devices and configuration using Python 3.7, along with cloud-based network management tasks using Python. As the book progresses, socket programming will be covered, followed by how to design servers, and the pros and cons of multithreaded and event-driven architectures. You'll develop practical clientside applications, including web API clients, email clients, SSH, and FTP. These applications will also be implemented through existing web application frameworks. What you will learn * Execute Python modules on networking tools * Automate tasks regarding the analysis and extraction of information from a network * Get to grips with asynchronous programming modules available in Python * Get to grips with IP address manipulation modules using Python programming * Understand the main frameworks available in Python that are focused on web application * Manipulate IP addresses and perform CIDR calculations Who this book is for If you're a Python developer or a system administrator with Python experience and you're looking to take your first steps in network programming, then this book is for you. If you're a network engineer or a network professional aiming to be more productive and efficient in networking programmability and automation then this book would serve as a useful resource. Basic knowledge of Python is assumed.