Author : Christoph Körner
Publisher : Packt Publishing Ltd
Page : 278 pages
File Size : 32,24 MB
Release : 2015-04-27
Category : Computers
ISBN : 1784395781
If you are a web developer with experience in AngularJS and want to implement interactive visualizations using D3.js, this book is for you. Knowledge of SVG or D3.js will give you an edge to get the most out of this book.
Author : Mike Dewar
Publisher : "O'Reilly Media, Inc."
Page : 73 pages
File Size : 24,1 MB
Release : 2012
Category : Computers
ISBN : 1449328792
Learn how to create beautiful, interactive, browser-based data visualizations with the D3 JavaScript library. This hands-on book shows you how to use a combination of JavaScript and SVG to build everything from simple bar charts to complex infographics. You'll learn how to use basic D3 tools by building visualizations based on real data from the New York Metropolitan Transit Authority. Using historical tables, geographical information, and other data, you'll graph bus breakdowns and accidents and the percentage of subway trains running on time, among other examples. By the end of the book, you'll be prepared to build your own web-based data visualizations with D3. Join a dataset with elements of a webpage, and modify the elements based on the data Map data values onto pixels and colors with D3's scale objects Apply axis and line generators to simplify aspects of building visualizations Create a simple UI that allows users to investigate and compare data Use D3 transitions in your UI to animate important aspects of the data Get an introduction to D3 layout tools for building more sophisticated visualizations If you can code and manipulate data, and know how to work with JavaScript and SVG, this book is for you.
Author : Ændrew H. Rininsland
Publisher : Packt Publishing Ltd
Page : 868 pages
File Size : 39,22 MB
Release : 2017-03-31
Category : Computers
ISBN : 1787286126
Turn your raw data into real knowledge by creating and deploying complex data visualizations with D3.js About This Book Understand how to best represent your data by developing the right kind of visualization Explore the concepts of D3.js through examples that enable you to quickly create visualizations including charts, network diagrams, and maps Get practical examples of visualizations using real-world data sets that show you how to use D3.js to visualize and interact with information to glean its underlying meaning Who This Book Is For Whether you are new to data and data visualization, a seasoned data scientist, or a computer graphics specialist, this Learning Path will provide you with the skills you need to create web-based and interactive data visualizations. Some basic JavaScript knowledge is expected, but no prior experience with data visualization or D3 is required What You Will Learn Gain a solid understanding of the common D3 development idioms Find out how to write basic D3 code for servers using Node.js Install and use D3.js to create HTML elements within a document Create and style graphical elements such as circles, ellipses, rectangles, lines, paths, and text using SVG Turn your data into bar and scatter charts, and add margins, axes, labels, and legends Use D3.js generators to perform the magic of creating complex visualizations from data Add interactivity to your visualizations, including tool-tips, sorting, hover-to-highlight, and grouping and dragging of visuals Write, test, and distribute a D3-based charting package Make a real-time application with Node and D3 In Detail D3 has emerged as one of the leading platforms to develop beautiful, interactive visualizations over the web. We begin the course by setting up a strong foundation, then build on this foundation as we take you through the entire world of reimagining data using interactive, animated visualizations created in D3.js. In the first module, we cover the various features of D3.js to build a wide range of visualizations. We also focus on the entire process of representing data through visualizations. By the end of this module, you will be ready to use D3 to transform any data into a more engaging and sophisticated visualization. In the next module, you will learn to master the creation of graphical elements from data. Using practical examples provided, you will quickly get to grips with the features of D3.js and use this learning to create your own spectacular data visualizations with D3.js. Over the last leg of this course, you will get acquainted with how to integrate D3 with mapping libraries to provide reverse geocoding and interactive maps among many other advanced features of D3. This module culminates by showing you how to create enterprise-level dashboards to display real-time data. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Learning D3.js Data Visualization, Second Edition by Andrew H. Rininsland D3.js By Example by Michael Heydt Mastering D3.js by Pablo Navarro Castillo Style and approach This course provides a comprehensive explanation of how to leverage the power of D3.js to create powerful and creative visualizations through step-by-step instructions in the form of modules. Each module help you skill up a level in creating meaningful visualizations.
Author : Christoph Korner
Publisher : Packt Publishing Ltd
Page : 258 pages
File Size : 48,84 MB
Release : 2016-03-23
Category : Computers
ISBN : 1785884336
Master the art of building responsive visualizations on the Web About This Book Learn the techniques for building data visualizations that work well for all screen sizes Implement responsive techniques with popular libraries to get to grips with building responsive visualizations that work in the real world Incorporate responsive workflow in your data visualization process to build visualizations that take a mobile-first approach. Who This Book Is For Web developers and data science professionals who want to make their visualizations work for smaller screen sizes. Some basic knowledge of JavaScript and Data visualization is expected. What You Will Learn Get familiar with responsive design for data visualizations Understand the main concepts of D3.js to create interactive visualizations Unleash the power of Bootstrap to create stunning and responsive visualizations for all screen resolutions Implement Touch and Mouse interactions for mobile-first applications Design Transitions and Animations that impress in portrait and landscape Build a Responsive World Map using GeoJSON and D3.js In Detail Using D3.js and Responsive Design principles, you will not just be able to implement visualizations that look and feel awesome across all devices and screen resolutions, but you will also boost your productivity and reduce development time by making use of Bootstrap—the most popular framework for developing responsive web applications. This book teaches the basics of scalable vector graphics (SVG), D3.js, and Bootstrap while focusing on Responsive Design as well as mobile-first visualizations; the reader will start by discovering Bootstrap and how it can be used for creating responsive applications, and then implement a basic bar chart in D3.js. You will learn about loading, parsing, and filtering data in JavaScript and then dive into creating a responsive visualization by using Media Queries, responsive interactions for Mobile and Desktop devices, and transitions to bring the visualization to life. In the following chapters, we build a fully responsive interactive map to display geographic data using GeoJSON and set up integration testing with Protractor to test the application across real devices using a mobile API gateway such as AWS Device Farm. You will finish the journey by discovering the caveats of mobile-first applications and learn how to master cross-browser complications. Style and approach As the world shifts to mobile devices for consuming data on the Web, developers are faced with the unique challenge of making data visualizations work for their smaller screens. The growth of responsive web design enabled developers to adopt page layouts and media for smaller screens, but there is still little information available on how to adapt data visualizations for the smaller screens. This book fills this important gap and shows how responsive web design principles can be extended to create visualizations that work well regardless of the screen size, thereby allowing developers to build user-friendly visualizations that work well on all devices. In addition to covering some of the popular techniques and design patterns for building responsive visualizations, the book also shows readers how to implement these techniques with the help of some popular tools and libraries.
Author : Scott Murray
Publisher : "O'Reilly Media, Inc."
Page : 269 pages
File Size : 42,12 MB
Release : 2013-03-15
Category : Computers
ISBN : 1449339735
Create and publish your own interactive data visualization projects on the Web, even if you have no experience with either web development or data visualization. It’s easy with this hands-on guide. You’ll start with an overview of data visualization concepts and simple web technologies, and then learn how to use D3, a JavaScript library that lets you express data as visual elements in a web page. Interactive Data Visualization for the Web makes these skills available at an introductory level for designers and visual artists without programming experience, journalists interested in the emerging data journalism processes, and others keenly interested in visualization and publicly available data sources. Get a practical introduction to data visualization, accessible for beginners Focus on web-based tools that help you publish your creations quickly to a wide audience Learn about interactivity so you can engage users in exploring your data
Author : Scott Murray
Publisher : "O'Reilly Media, Inc."
Page : 472 pages
File Size : 37,65 MB
Release : 2017-08-03
Category : Computers
ISBN : 1491921323
Author Scott Murray teaches you the fundamental concepts and methods of D3, a JavaScript library that lets you express data visually in a web browser.
Author : Borko Furht
Publisher : Springer
Page : 405 pages
File Size : 42,3 MB
Release : 2016-09-16
Category : Computers
ISBN : 3319445502
The objective of this book is to introduce the basic concepts of big data computing and then to describe the total solution of big data problems using HPCC, an open-source computing platform. The book comprises 15 chapters broken into three parts. The first part, Big Data Technologies, includes introductions to big data concepts and techniques; big data analytics; and visualization and learning techniques. The second part, LexisNexis Risk Solution to Big Data, focuses on specific technologies and techniques developed at LexisNexis to solve critical problems that use big data analytics. It covers the open source High Performance Computing Cluster (HPCC Systems®) platform and its architecture, as well as parallel data languages ECL and KEL, developed to effectively solve big data problems. The third part, Big Data Applications, describes various data intensive applications solved on HPCC Systems. It includes applications such as cyber security, social network analytics including fraud, Ebola spread modeling using big data analytics, unsupervised learning, and image classification. The book is intended for a wide variety of people including researchers, scientists, programmers, engineers, designers, developers, educators, and students. This book can also be beneficial for business managers, entrepreneurs, and investors.
Author : Christoph Korner
Publisher : Packt Publishing
Page : 278 pages
File Size : 45,80 MB
Release : 2015-04-30
Category : Computers
ISBN : 9781784398484
Author : Christoph Körner
Publisher : Packt Publishing Ltd
Page : 437 pages
File Size : 23,94 MB
Release : 2020-04-30
Category : Computers
ISBN : 1789801524
Master expert techniques for building automated and highly scalable end-to-end machine learning models and pipelines in Azure using TensorFlow, Spark, and Kubernetes Key FeaturesMake sense of data on the cloud by implementing advanced analyticsTrain and optimize advanced deep learning models efficiently on Spark using Azure DatabricksDeploy machine learning models for batch and real-time scoring with Azure Kubernetes Service (AKS)Book Description The increase being seen in data volume today requires distributed systems, powerful algorithms, and scalable cloud infrastructure to compute insights and train and deploy machine learning (ML) models. This book will help you improve your knowledge of building ML models using Azure and end-to-end ML pipelines on the cloud. The book starts with an overview of an end-to-end ML project and a guide on how to choose the right Azure service for different ML tasks. It then focuses on Azure Machine Learning and takes you through the process of data experimentation, data preparation, and feature engineering using Azure Machine Learning and Python. You'll learn advanced feature extraction techniques using natural language processing (NLP), classical ML techniques, and the secrets of both a great recommendation engine and a performant computer vision model using deep learning methods. You'll also explore how to train, optimize, and tune models using Azure Automated Machine Learning and HyperDrive, and perform distributed training on Azure. Then, you'll learn different deployment and monitoring techniques using Azure Kubernetes Services with Azure Machine Learning, along with the basics of MLOps—DevOps for ML to automate your ML process as CI/CD pipeline. By the end of this book, you'll have mastered Azure Machine Learning and be able to confidently design, build and operate scalable ML pipelines in Azure. What you will learnSetup your Azure Machine Learning workspace for data experimentation and visualizationPerform ETL, data preparation, and feature extraction using Azure best practicesImplement advanced feature extraction using NLP and word embeddingsTrain gradient boosted tree-ensembles, recommendation engines and deep neural networks on Azure Machine LearningUse hyperparameter tuning and Azure Automated Machine Learning to optimize your ML modelsEmploy distributed ML on GPU clusters using Horovod in Azure Machine LearningDeploy, operate and manage your ML models at scaleAutomated your end-to-end ML process as CI/CD pipelines for MLOpsWho this book is for This machine learning book is for data professionals, data analysts, data engineers, data scientists, or machine learning developers who want to master scalable cloud-based machine learning architectures in Azure. This book will help you use advanced Azure services to build intelligent machine learning applications. A basic understanding of Python and working knowledge of machine learning are mandatory.
Author : Christoph Korner
Publisher : Packt Publishing Ltd
Page : 624 pages
File Size : 43,5 MB
Release : 2022-05-10
Category : Computers
ISBN : 1803246790
Supercharge and automate your deployments to Azure Machine Learning clusters and Azure Kubernetes Service using Azure Machine Learning services Key Features Implement end-to-end machine learning pipelines on Azure Train deep learning models using Azure compute infrastructure Deploy machine learning models using MLOps Book Description Azure Machine Learning is a cloud service for accelerating and managing the machine learning (ML) project life cycle that ML professionals, data scientists, and engineers can use in their day-to-day workflows. This book covers the end-to-end ML process using Microsoft Azure Machine Learning, including data preparation, performing and logging ML training runs, designing training and deployment pipelines, and managing these pipelines via MLOps. The first section shows you how to set up an Azure Machine Learning workspace; ingest and version datasets; as well as preprocess, label, and enrich these datasets for training. In the next two sections, you'll discover how to enrich and train ML models for embedding, classification, and regression. You'll explore advanced NLP techniques, traditional ML models such as boosted trees, modern deep neural networks, recommendation systems, reinforcement learning, and complex distributed ML training techniques - all using Azure Machine Learning. The last section will teach you how to deploy the trained models as a batch pipeline or real-time scoring service using Docker, Azure Machine Learning clusters, Azure Kubernetes Services, and alternative deployment targets. By the end of this book, you'll be able to combine all the steps you've learned by building an MLOps pipeline. What you will learn Understand the end-to-end ML pipeline Get to grips with the Azure Machine Learning workspace Ingest, analyze, and preprocess datasets for ML using the Azure cloud Train traditional and modern ML techniques efficiently using Azure ML Deploy ML models for batch and real-time scoring Understand model interoperability with ONNX Deploy ML models to FPGAs and Azure IoT Edge Build an automated MLOps pipeline using Azure DevOps Who this book is for This book is for machine learning engineers, data scientists, and machine learning developers who want to use the Microsoft Azure cloud to manage their datasets and machine learning experiments and build an enterprise-grade ML architecture using MLOps. This book will also help anyone interested in machine learning to explore important steps of the ML process and use Azure Machine Learning to support them, along with building powerful ML cloud applications. A basic understanding of Python and knowledge of machine learning are recommended.
