Master scientific computing with NumPy using Packt's NumPy Cookbook

November 2012 | Cookbooks, Open Source

Packt is pleased to announce its second book on NumPy; it's titled "NumPy Cookbook". The book is filled with practical recipes that will take Python developers with basic NumPy skills to next level. From this book of Ivan Idris, an Msc in Experimental Physics; readers will learn to do high performance calculations with clean and efficient Numpy Codes, analyze large sets of data with statistical functions and compute complex linear algebra.

NumPy Cookbook will teach its readers to write readable, efficient and fast code with the cutting edge open source Numpy Software library. This unique cookbook will deliver learning about advanced indexing and linear algebra. The technology will provide guidance in profiling NumPy code and visualize the profiling results. It will speed coding with Cython. Use of array interface to expose foreign memory to NumPy and use of universal functions and interoperability features has also been explained with ease. Plotting with Matplotlib and related SciPy project which is often used in conjunction with Numpy is also being explained with the help of examples thus making its understanding pretty simple.

This book will give a solid foundation in Numpy, a leading scientific computing library. NumPy replaces a lot of the functionality of Matlab and Mathematica, but unlike these products, it is free and open source. The book will teach about installing and using NumPy related concepts. Practical recipes in book will make understanding of the solutions to each problem much easier, thus helping Python developers to reach the next level with NumPy skills.

Numpy Cookbook is out now and available from Packt in print and popular e-book formats. To read more about it and download a sample chapter, please visit the Packt web-page.

 

NumPy Cookbook
Over 70 interesting recipes for learning the Python open source mathematical library, NumPy

For more information, please visit: NumPy Cookbook

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