Jon L. Dunn Bücher

The most up-to-date and comprehensive source on North American bird identification, distribution, behavior, habitat, and conservation concerns available today.

The book caters to the growing interest in birding by providing tailored field guides for birders on either side of the Rocky Mountains. Each volume offers comprehensive information on all officially recorded birds in the region, featuring illustrated accounts of various plumages and life stages. Additionally, it includes hundreds of color-coded range maps, enhancing the birding experience for both new and seasoned enthusiasts.

National Geographic Field Guide to the Birds of North America continues to be the most sought-after, the most authoritative, and the easiest to access field guide to birds on the market. Now in its 4th Edition, revisions include 250 updated range maps, and new classification information National Geographic is reissuing the Field Guide to the Birds of North America in the 4th edition, focusing on its accuracy and easy use in the field. This is the ultimate birders field guide - sturdy, easy to carry and use, and featuring the most complete information among bird guides. It features all species known to breed in North America, including those that are regular visitors to our continent or that drop in occasionally - more than 800 in all. The edition is lavishly illustrated with specially commissioned full-colour illustrations, plus newly updated range maps and detailed descriptions. A superb new index allows birders in the field to quickly identify a species.

This comprehensive handbook serves as an essential resource for novice and intermediate birding enthusiasts, detailing key techniques for identifying and locating various bird species. It covers the use of field guides, essential equipment, and how to interpret range maps. Additionally, the book explores birds' physical features, classification, and includes recommendations for further reading to enhance one's birding knowledge and library.

Corpus analysis can be expanded and scaled up by incorporating computational methods from natural language processing. This Element shows how text classification and text similarity models can extend our ability to undertake corpus linguistics across very large corpora.

This Element introduces a usage-based computational approach to Construction Grammar that draws on techniques from natural language processing and unsupervised machine learning. The computational experiments are important for testing the learnability, variability, and confirmability of Construction Grammar as a theory of language.