Introduction To Geospatial Technologies

Author: Bradley A. Shellito
Publisher: Macmillan Higher Education
ISBN: 9781464134371
Size: 11.71 MB
Format: PDF, ePub
View: 65

Combining both theoretical coverage and hands-on lab work, and accessible to majors and non-majors alike, Bradley Shellito's Introduction to Geospatial Technologies has become a new favorite for the digital Earth course. The new edition reflects the latest developments in the field, including how scientists are using GIS data with cloud technology. With lab activities that utilize both widely available freeware and ArcGIS, instructors can tailor the course to their students. Introduction to Geospatial Technologies, Second Edition is available in three formats: a paperback edition, a loose-leaf edition, and a fully interactive e-Book.

Integrating Educational Technology Into Teaching

Author: M. D. Roblyer
Publisher: Pearson
ISBN: 9780133972030
Size: 10.79 MB
Format: PDF, ePub
View: 77

Note: This is the loose-leaf version of Integrating Educational Technology into Teaching and does not include access to the Enhanced Pearson eText. To order the Enhanced Pearson eText packaged with the loose-leaf version, use ISBN 0134046919. This widely popular resource balances the theory-based “why” and the practical “how” of using technology to support and shape the future of technology in education. In it, readers see how technology integration strategies link to specific learning theories and how teachers can plan for technology integration, complete with opportunities to practice integrating technology by designing curriculum to meet teaching and learning needs. Integrating Educational Technology into Teaching’s comprehensive technology integration framework—The Technology Integration Planning Model (TIP Model)—is built on a balance of research and proven classroom practices and shows teachers how to create an environment in which technology can effectively enhance learning. Carefully-selected examples and exercises in each chapter encourage teachers to reflect on their practice as they develop the insights, knowledge, and skills they need to integrate technology into content area curricula. Featured are hundreds of lesson examples and recommended resources. The Enhanced Pearson eText features embedded video, Interactive Technology Learning Checklists and exercises, author-recorded Big Ideas overviews, and additional classroom-ready example assessments. Improve mastery and retention with the Enhanced Pearson eText* The Enhanced Pearson eText provides a rich, interactive learning environment designed to improve student mastery of content. The Enhanced Pearson eText is: Engaging. The new interactive, multimedia learning features were developed by the authors and other subject-matter experts to deepen and enrich the learning experience. Convenient. Enjoy instant online access from your computer or download the Pearson eText App to read on or offline on your iPad® and Android® tablet.* Affordable. Experience the advantages of the Enhanced Pearson eText along with all the benefits of print for 40% to 50% less than a print bound book. * The Enhanced eText features are only available in the Pearson eText format. They are not available in third-party eTexts or downloads. *The Pearson eText App is available on Google Play and in the App Store. It requires Android OS 3.1-4, a 7” or 10” tablet, or iPad iOS 5.0 or later.

Introduction To Machine Learning

Author: Ethem Alpaydin
Publisher: MIT Press
ISBN: 9780262028189
Size: 16.97 MB
Format: PDF, ePub
View: 35

The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, optimize robot behavior so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data. Introduction to Machine Learning is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts. Subjects include supervised learning; Bayesian decision theory; parametric, semi-parametric, and nonparametric methods; multivariate analysis; hidden Markov models; reinforcement learning; kernel machines; graphical models; Bayesian estimation; and statistical testing.Machine learning is rapidly becoming a skill that computer science students must master before graduation. The third edition of Introduction to Machine Learning reflects this shift, with added support for beginners, including selected solutions for exercises and additional example data sets (with code available online). Other substantial changes include discussions of outlier detection; ranking algorithms for perceptrons and support vector machines; matrix decomposition and spectral methods; distance estimation; new kernel algorithms; deep learning in multilayered perceptrons; and the nonparametric approach to Bayesian methods. All learning algorithms are explained so that students can easily move from the equations in the book to a computer program. The book can be used by both advanced undergraduates and graduate students. It will also be of interest to professionals who are concerned with the application of machine learning methods.

Visualizing Weather And Climate

Author: Bruce Anderson
Publisher: Wiley Global Education
ISBN: 9781118308851
Size: 17.89 MB
Format: PDF
View: 84

Visualizing Weather and Climate offers students a valuable opportunity to identify and connect the central issues of weather, climate, and the atmosphere through a visual approach. The text is organized around the premise that weather and climate are two interrelated and equally important influences upon environmental processes and human activity. As students explore the critical topics of weather and climate, their study of the role of the atmosphere is interwoven with the behavior of the oceans, land surfaces, ecosystems, and human activity. Visualizing Weather and Climate integrates visuals with text to elucidate concepts for students and solidify their understanding of them. The accessible format allows students to navigate through the material with greater ease.

Computer Vision

Author: Richard Szeliski
Publisher: Springer Science & Business Media
ISBN: 1848829353
Size: 13.50 MB
Format: PDF, Kindle
View: 60

Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos. More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are also analyzed using statistical models and solved using rigorous engineering techniques. Topics and features: structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses; presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects; provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, and Bayesian estimation theory; suggests additional reading at the end of each chapter, including the latest research in each sub-field, in addition to a full Bibliography at the end of the book; supplies supplementary course material for students at the associated website, http://szeliski.org/Book/. Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.

Introduction To Geographic Information Systems

Author: Kang-tsung Chang
Publisher: McGraw-Hill Higher Education
ISBN: 9781259613449
Size: 10.20 MB
Format: PDF, Docs
View: 67

Introduction to Geographic Information Systems, 8th edition is designed to provide students in a first or second GIS course with a solid foundation in both GIS concepts and the use of GIS. Introduction to GIS strikes a careful balance between GIS concepts and hands-on applications. The main portion of the chapter presents GIS terms and concepts and helps students learn how each one fits into a complete GIS system. At the end of each chapter, an application section with 2-7 tasks presents students with actual GIS exercises and the necessary data to solve the problem.

Biodesign

Author: Stefanos Zenios
Publisher: Cambridge University Press
ISBN: 9780521517423
Size: 16.75 MB
Format: PDF, Kindle
View: 97

Recognize market opportunities, master the design process, and develop business acumen with this 'how-to' guide to medical technology innovation. Outlining a systematic, proven approach for innovation - identify, invent, implement - and integrating medical, engineering, and business challenges with real-world case studies, this book provides a practical guide for students and professionals.