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