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SciPy and NumPy

by Eli Bressert

<p>Want to learn SciPy and NymPy quickly? Cut through the complexity of online documentation with this concise and illustrated book, and discover how easily you can get up to speed with these Python libraries. You&#8217;ll understand why they&#8217;re powerful enough for many of today&#8217;s leading scientists and engineers.</p>

SciPy and NumPy

by Eli Bressert

Are you new to SciPy and NumPy? Do you want to learn it quickly and easily through examples and a concise introduction? Then this is the book for you. You'll cut through the complexity of online documentation and discover how easily you can get up to speed with these Python libraries. Ideal for data analysts and scientists in any field, this overview shows you how to use NumPy for numerical processing, including array indexing, math operations, and loading and saving data. You'll learn how SciPy helps you work with advanced mathematical functions such as optimization, interpolation, integration, clustering, statistics, and other tools that take scientific programming to a whole new level. Discover why these tools are powerful enough for many of today's leading scientists and engineers. This book also introduces add-on SciKits packages that focus on advanced imaging algorithms and machine learning. All of the examples are provided as python scripts so you can explore and use the code to your liking.riety of SciPy statistical tools such as distributions and functions Learn SciPy's spatial and cluster analysis classes Save operation time and memory usage with sparse matrices Delve into scikits-image for advanced imaging capabilities, and scikits-learn for machine learning and data mining

SciPy and NumPy

by Eli Bressert

Are you new to SciPy and NumPy? Do you want to learn it quickly and easily through examples and a concise introduction? Then this is the book for you. You'll cut through the complexity of online documentation and discover how easily you can get up to speed with these Python libraries. Ideal for data analysts and scientists in any field, this overview shows you how to use NumPy for numerical processing, including array indexing, math operations, and loading and saving data. You'll learn how SciPy helps you work with advanced mathematical functions such as optimization, interpolation, integration, clustering, statistics, and other tools that take scientific programming to a whole new level. The new edition is now available, fully revised and updated in June 2013. Learn the capabilities of NumPy arrays, element-by-element operations, and core mathematical operations Solve minimization problems quickly with SciPy's optimization package Use SciPy functions for interpolation, from simple univariate to complex multivariate cases Apply a variety of SciPy statistical tools such as distributions and functions Learn SciPy's spatial and cluster analysis classes Save operation time and memory usage with sparse matrices

Showing 1 through 3 of 3 results

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