Power Quick Reference

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This work follows the 2021 curriculum of the Association for Computing Machinery for specialists in Data Sciences, with the aim of producing a manual that collects notions in a simplified form, facilitating a personal training path starting from specialized skills in Computer Science or Mathematics or Statistics. It has a bibliography with links to quality material but freely usable for your own training and contextual practical exercises. Second of a series of books, it covers methodological aspects, analysis and visualization. It describes the CRISP DM methodology, the working phases, the success criteria, the languages and the environments that can be used, the application libraries. Since this book uses Orange for the application aspects, its installation and widgets are described. In visualization, historical notes are made, and next the book describes the characteristics of an effective visualization, the types of messages that can be conveyed, the Grammar of Graphics, the use of a graph and a dashboard, the software and libraries that can be used, the role and use of color. 55 types of graphs are then analyzed, reporting meaning, use, examples and visual dimensions also with a vocabulary of graphs and summary tables. Examples are given in Orange and the possible use of Python with Orange is explained. Visualization-based inference is discussed, exploratory and confirmatory analysis is defined and techniques are reported. The book is accompanied by supporting material and it is possible to download the project samples in Orange and sample data.

Time is of the essence on the electrical PE exam, and Electrical Engineering Quick Reference for the Power, Electrical and Electronics, and Computer PE Exams helps you best utilize each minute by putting the information you need the most at your fingertips. Using an exam-friendly format, Electrical Engineering Quick Reference logically organizes all the formulas and data from the Electrical Engineering Reference Manual that are likely to be used during the exam. Many exam problems can be solved using the Electrical Engineering Quick Reference alone. If you require more information, you can quickly refer to the Reference Manual as formulas and data are fully indexed for rapid retrieval. Electrical Engineering Quick Reference has been updated to the 8th edition of the Electrical Engineering Reference Manual and covers the topics found on the Power, Electrical and Electronics, and Computer PE exams. Electrical Engineering Quick Reference saves you precious exam time by * Putting the data you need the most at your fingertips * Isolating the most useful equations and formulas in the Reference Manual * Allowing you to quickly retrieve formulas without the distraction of surrounding text * Cross-referencing additional information to the Reference Manual _____________________________ Since 1975 more than 2 million people preparing for their engineering, surveying, architecture, LEED®, interior design, and landscape architecture exams have entrusted their exam prep to PPI. For more information, visit us at www.ppi2pass.com.

"From the publishers of Tarascon Pocket Pharmacopoeia."

HTML, or hypertext mark-up language, is the standard for all world wide web pages throughout the world. With HTML 3.0 new features have been added and in addition VRML, the virtual reality mark-up language, is also attracting attention to enable browsers to move through "virtual reality" web sites. This book provides a reference guide to both HTML and VRML modelled on the author's previous successful reference guides to AutoCad. Each HTML and VRMl command is given a description, its syntax, and examples of its use. - Visual snapshots of each markup in use.- Each HTML tag is marked with its version number to highlight the new 3.0 features.- Covers all the known VRML tags for 2.0.- Examples cover related and optional attributes.

This work follows the 2021 curriculum of the Association for Computing Machinery for specialists in Data Sciences, with the aim of producing a manual that collects notions in a simplified form, facilitating a personal training path starting from specialized skills in Computer Science or Mathematics or Statistics. It has a bibliography with links to quality material but freely usable for your own training and contextual practical exercises. Part of a series of books, it first summarizes the standard CRISP DM working methodology used in this work and in Data Science projects. Since this text uses Orange for the application aspects, it describes its installation and widgets. Then it considers the concept of model, its life cycle and the relationship with measures and metrics. The data modeling phase is considered from the point of view of machine learning by deepening the types of machine learning, the types of models, the types of problems and the types of algorithms. After considering the ideal characteristics of models and algorithms, a vocabulary of the types of models and algorithms is compiled and their use in Orange is considered through two supervised and unsupervised projects respectively. The text is accompanied by supporting material and you can download the samples in Orange and the test data.