Download Free Visual Explanations Book in PDF and EPUB Free Download. You can read online Visual Explanations and write the review.

Display of information for paper and computer screens; principles of information design, design of presentations. Depicting evidence relevant to cause and effect, decision making. Scientific visualization.
Escaping flatland -- Micro/macro readings -- Layering and separation -- Small multiples -- Color and information -- Narratives and space and time -- Epilogue.
This radical first course on complex analysis brings a beautiful and powerful subject to life by consistently using geometry (not calculation) as the means of explanation. Aimed at undergraduate students in mathematics, physics, and engineering, the book's intuitive explanations, lack of advanced prerequisites, and consciously user-friendly prose style will help students to master the subject more readily than was previously possible. The key to this is the book's use of new geometric arguments in place of the standard calculational ones. These geometric arguments are communicated with the aid of hundreds of diagrams of a standard seldom encountered in mathematical works. A new approach to a classical topic, this work will be of interest to students in mathematics, physics, and engineering, as well as to professionals in these fields.
How seeing turns into showing, how empirical observations turn into explanation and evidence. How to produce and consume evidence presentations.
Escaping flatland -- Micro/macro readings -- Layering and separation -- Small multiples -- Color and information -- Narratives and space and time -- Epilogue.
Introduction to data analysis; Predictions and projections: some issues of research design; Two-variable linear regression; Multiple regression.
Best practices and step-by-step instructions for using the Tableau Software toolset Although the Tableau Desktop interface is relatively intuitive, this book goes beyond the simple mechanics of the interface to show best practices for creating effective visualizations for specific business intelligence objectives. It illustrates little-known features and techniques for getting the most from the Tableau toolset, supporting the needs of the business analysts who use the product as well as the data and IT managers who support it. This comprehensive guide covers the core feature set for data analytics, illustrating best practices for creating and sharing specific types of dynamic data visualizations. Featuring a helpful full-color layout, the book covers analyzing data with Tableau Desktop, sharing information with Tableau Server, understanding Tableau functions and calculations, and Use Cases for Tableau Software. Includes little-known, as well as more advanced features and techniques, using detailed, real-world case studies that the author has developed as part of his consulting and training practice Explains why and how Tableau differs from traditional business information analysis tools Shows you how to deploy dashboards and visualizations throughout the enterprise Provides a detailed reference resource that is aimed at users of all skill levels Depicts ways to leverage Tableau across the value chain in the enterprise through case studies that target common business requirements Endorsed by Tableau Software Tableau Your Data shows you how to build dynamic, best-of-breed visualizations using the Tableau Software toolset.
This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.
The eight-volume set comprising LNCS volumes 9905-9912 constitutes the refereed proceedings of the 14th European Conference on Computer Vision, ECCV 2016, held in Amsterdam, The Netherlands, in October 2016. The 415 revised papers presented were carefully reviewed and selected from 1480 submissions. The papers cover all aspects of computer vision and pattern recognition such as 3D computer vision; computational photography, sensing and display; face and gesture; low-level vision and image processing; motion and tracking; optimization methods; physicsbased vision, photometry and shape-from-X; recognition: detection, categorization, indexing, matching; segmentation, grouping and shape representation; statistical methods and learning; video: events, activities and surveillance; applications. They are organized in topical sections on detection, recognition and retrieval; scene understanding; optimization; image and video processing; learning; action activity and tracking; 3D; and 9 poster sessions.