If you are a web developer with a basic knowledge of HTML, CSS, and JavaScript and want to quickly get started with this web charting technology, this is the book for you. This book will also serve as an essential guide to those who have probably used a similar library and are now looking at migrating to Highcharts.

The book is aimed at all levels of readers. Beginners can learn the basic configurations and step-by-step approaches in creating charts or Highcharts cloud. For intermediate and advanced readers, the book explores the APIs, events, server-side operations and plugins.

If you are an Ext JS or Sencha Touch developer, designer, or architect who wants to build enterprise-scale data visualization capabilities using Sencha, then this book is ideal for you. You should have a knowledge of HTML, JavaScript, CSS, and Sencha Ext JS or Sencha Touch fundamentals, in particular. Some familiarity with SVG and HTML5 Canvas would be preferred, but not required.

Learn to create stunning animated and interactive charts using Highcharts and Angular. Use and build on your existing knowledge of HTML, CSS, and JavaScript to develop impressive dashboards that will work in all modern browsers. You will learn how to use Highcharts, call backend services for data, and easily construct real-time data dashboards. You'll also learn how you can club your code with jQuery and Angular. This book provides the best solutions for real-time challenges and covers a wide range of charts including line, area, maps, plot, different types of pie chart, Gauge, heat map, Histogram, stacked bar, scatter plot and 3d charts. After reading this book, you'll be able to export your charts in different formats for project-based learning. Highcharts is one the most useful products worldwide for develop charting on the web, and Angular is well known for speed. Using Highcharts with Angular, developers can build fast, interactive dashboards. Get up to speed using this book today. What You’ll Learn How to develop interactive, animated dashboards How you can implement Highcharts using Angular How to develop a real-time application with the use of WebAPI, Angular, and Highcharts How to create interactive styling themes and colors for a dashboard Who This Book Is For This book is aimed at developers, dev leads, software architects, students or enthusiasts who are already familiar with HTML, CSS, and JavaScript.

Through hundreds of photographs, this dynamic guide demonstrates how to expertly apply design principles in a variety of devices, desktops, web pages, mobile and other touchscreen devices.

In an era of big data and data analytics, how can managers make decisions based on almost unlimited information, not to mention hiring and retaining individuals with the required data analytics skills? The new fourth edition of Essentials of Business Research Methods explains research methods and analytical techniques for individuals who aren't data scientists. The authors offer a straightforward, hands-on approach to the vital managerial process of gathering and using data to make relevant and timely business decisions. They include critical topics, such as the increasing role of online research, ethical issues, privacy matters, data analytics, customer relationship management, how to conduct information-gathering activities more effectively in a rapidly changing business environment, and more. This is also the only text that includes a chapter on qualitative data analysis, and the coverage of quantitative data analysis is more extensive as well as much easier to understand than in other texts. A realistic continuing case used throughout the book, applied research examples, and ethical dilemma mini cases enable upper-level undergraduate and postgraduate students to see how business research information is used in the real world. This comprehensive textbook is supported by a range of online resources, including instructors’ manuals, PowerPoint slides, and test banks.

Get up and running with machine learning with F# in a fun and functional way About This Book Design algorithms in F# to tackle complex computing problems Be a proficient F# data scientist using this simple-to-follow guide Solve real-world, data-related problems with robust statistical models, built for a range of datasets Who This Book Is For If you are a C# or an F# developer who now wants to explore the area of machine learning, then this book is for you. Familiarity with theoretical concepts and notation of mathematics and statistics would be an added advantage. What You Will Learn Use F# to find patterns through raw data Build a set of classification systems using Accord.NET, Weka, and F# Run machine learning jobs on the Cloud with MBrace Perform mathematical operations on matrices and vectors using Math.NET Use a recommender system for your own problem domain Identify tourist spots across the globe using inputs from the user with decision tree algorithms In Detail The F# functional programming language enables developers to write simple code to solve complex problems. With F#, developers create consistent and predictable programs that are easier to test and reuse, simpler to parallelize, and are less prone to bugs. If you want to learn how to use F# to build machine learning systems, then this is the book you want. Starting with an introduction to the several categories on machine learning, you will quickly learn to implement time-tested, supervised learning algorithms. You will gradually move on to solving problems on predicting housing pricing using Regression Analysis. You will then learn to use Accord.NET to implement SVM techniques and clustering. You will also learn to build a recommender system for your e-commerce site from scratch. Finally, you will dive into advanced topics such as implementing neural network algorithms while performing sentiment analysis on your data. Style and approach This book is a fast-paced tutorial guide that uses hands-on examples to explain real-world applications of machine learning. Using practical examples, the book will explore several machine learning techniques and also describe how you can use F# to build machine learning systems.