Shapiro bruce e (8 Ergebnisse)

Zustand: Good. Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc.

Paperback. Zustand: Fair. Illustrated. The item might be beaten up but readable. May contain markings or highlighting, as well as stains, bent corners, or any other major defect, but the text is not obscured in any way.

Zustand: Fine. Used book that is in almost brand-new condition. May contain a remainder mark. Better World Books: Buy Books. Do Good.

Zustand: Very Good. 130 pp., Hardcover, some wear to corners else text clean & binding tight. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country.…

Softcover. Zustand: Very Good. Magazine. Quarto. 94pp. Perfectbound. Soiling and light foxing, very good. Notable contributors include Kay Boyle, Bruce Cutler, Hazel E. Barnes, Nolan Miller, Felix Clowder, Ihab H. Hassan, A.M. Tibbetts, and more.

Zustand: New. pp. 480.

Zustand: New.

Taschenbuch. Zustand: Neu. Neuware - There is a newer edition (ISBN 978-1725894662) of this book that actually covers Python 3.6. This is a book about hacking, but not just any kind of hacking. It is about mathematical hacking, or scientific computing. If you like math and want to use computers to do math or solve mathematical problems, then this book is the for you. This is version 3, which includes over 80 additional pages, with extensive additions on Python classes, iPython with jupyter not Elektronisches Buch, magic functions, random numbers, and probability and statistics. The emphasis throughout the text is on programming in the iPython notebook. Version 3.0.3 (2017) is revised and corrected. Part I gives an introduction to programming, the Python shell, and using iPython not Elektronisches Buch. Part II gives a thorough tour of the Python language. Topics include data types, simple statements, assignments, conditionals, loops, list comprehension, sorting, Numpy, pyplot, using dictionaries, functions, classes, functional programs, lambda functions, and recursion. Part III gives applications, including probability and statistics, and topics from machine learning such as clustering, linear regression, logistic regression and principal component analysis. Other topics include image analysis, the singular value decomposition, solving initial value problems, discrete systems, fractals, estimating pi, geographic maps, and satellite orbit analysis. Over 300 problems are included that can be used for student programming projects. No programming background required. Some basic understanding of math through calculus expected for the applications.…