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More Math Into LaTeX

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	More Math Into LaTeX/ by George Grätzer.
作者:	Grätzer, George.
面頁冊數:	XXX, 609 p. 76 illus., 23 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Natural language processing (Computer science). -
電子資源:	https://doi.org/10.1007/978-3-319-23796-1
ISBN:	9783319237961

More Math Into LaTeX
Grätzer, George.

More Math Into LaTeX[electronic resource] /by George Grätzer. - 5th ed. 2016. - XXX, 609 p. 76 illus., 23 illus. in color.online resource.

For over two decades, this comprehensive manual has been the standard introduction and complete reference for writing articles and books containing mathematical formulas. If the reader requires a streamlined approach to learning LaTeX for composing everyday documents, Grätzer’s © 2014 Practical LaTeX may also be a good choice. In this carefully revised fifth edition, the Short Course has been brought up to date and reflects a modern and practical approach to LaTeX usage. New chapters have been added on illustrations and how to use LaTeX on an iPad. Key features: An example-based, visual approach and a gentle introduction with the Short Course A detailed exposition of multiline math formulas with a Visual Guide A unified approach to TeX, LaTeX, and the AMS enhancements A quick introduction to creating presentations with formulas From earlier reviews: Grätzer’s book is a solution. —European Mathematical Society Newsletter There are several LaTeX guides, but this one wins hands down for the elegance of its approach and breadth of coverage. —Amazon.com, Best of 2000, Editor’s choice A novice reader will be able to learn the most essential features of LaTeX sufficient to begin typesetting papers within a few hours of time… An experienced TeX user, on the other hand, will find a systematic and d etailed discussion of LaTeX features. —Report on Mathematical Physics A very helpful and useful tool for all scientists and engineers. —Review of Astronomical Tools.

ISBN: 9783319237961

Standard No.: 10.1007/978-3-319-23796-1doiSubjects--Topical Terms:

802180
Natural language processing (Computer science).

LC Class. No.: QA76.9.N38

Dewey Class. No.: 006.35

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