Home | Amazing | Today | Tags | Publishers | Years | Account | Search 
Visual Insights: A Practical Guide to Making Sense of Data (The MIT Press)

Buy

A guide to the basics of information visualization that teaches nonprogrammers how to use advanced data mining and visualization techniques to design insightful visualizations.

In the age of Big Data, the tools of information visualization offer us a macroscope to help us make sense of the avalanche of data available on every subject. This book offers a gentle introduction to the design of insightful information visualizations. It is the only book on the subject that teaches nonprogrammers how to use open code and open data to design insightful visualizations. Readers will learn to apply advanced data mining and visualization techniques to make sense of temporal, geospatial, topical, and network data.

The book, developed for use in an information visualization MOOC, covers data analysis algorithms that enable extraction of patterns and trends in data, with chapters devoted to “when” (temporal data), “where” (geospatial data), “what” (topical data), and “with whom” (networks and trees); and to systems that drive research and development. Examples of projects undertaken for clients include an interactive visualization of the success of game player activity in World of Warcraft; a visualization of 311 number adoption that shows the diffusion of non-emergency calls in the United States; a return on investment study for two decades of HIV/AIDS research funding by NIAID; and a map showing the impact of the HiveNYC Learning Network.

Visual Insights will be an essential resource on basic information visualization techniques for scholars in many fields, students, designers, or anyone who works with data.

(HTML tags aren't allowed.)

Deep Learning Cookbook: Practical Recipes to Get Started Quickly
Deep Learning Cookbook: Practical Recipes to Get Started Quickly

Deep learning doesn’t have to be intimidating. Until recently, this machine-learning method required years of study, but with frameworks such as Keras and Tensorflow, software engineers without a background in machine learning can quickly enter the field. With the recipes in this cookbook, you’ll learn how to solve...

Mastering AutoCAD 2019 and AutoCAD LT 2019
Mastering AutoCAD 2019 and AutoCAD LT 2019

The world’s favorite guide to everything AutoCAD and AutoCAD LT—updated for 2019!

Mastering AutoCAD 2019 and AutoCAD LT 2019 is the world’s all-time best-selling guide to the world’s most popular drafting software. Packed with tips, tricks, techniques, and tutorials, this guide covers every...

PMI-ACP Project Management Institute Agile Certified Practitioner Exam Study Guide
PMI-ACP Project Management Institute Agile Certified Practitioner Exam Study Guide

The ultimate study package for the new PMI-ACP exam

The PMI-ACP Project Management Institute Agile Certified Practitioner Exam Study Guide is an all-in-one package for comprehensive exam preparation. This up-to-date guide is fully aligned with the latest version of the exam, featuring coverage of 100 percent of the...


Applied Text Analysis with Python: Enabling Language-Aware Data Products with Machine Learning
Applied Text Analysis with Python: Enabling Language-Aware Data Products with Machine Learning

From news and speeches to informal chatter on social media, natural language is one of the richest and most underutilized sources of data. Not only does it come in a constant stream, always changing and adapting in context; it also contains information that is not conveyed by traditional data sources. The key to unlocking natural...

Windows Security Monitoring: Scenarios and Patterns
Windows Security Monitoring: Scenarios and Patterns

Dig deep into the Windows auditing subsystem to monitor for malicious activities and enhance Windows system security

Written by a former Microsoft security program manager, DEFCON "Forensics CTF" village author and organizer, and CISSP, this book digs deep into the Windows security auditing subsystem to help you...

Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists
Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists

Feature engineering is a crucial step in the machine-learning pipeline, yet this topic is rarely examined on its own. With this practical book, you’ll learn techniques for extracting and transforming features—the numeric representations of raw data—into formats for machine-learning models. Each chapter guides you...

©2019 LearnIT (support@pdfchm.net) - Privacy Policy