Packt is pleased to announce the release of its new book, titled Learning SciPy for Numerical and Scientific Computing a comprehensive guide that lets readers master powerful mathematical and scientific computing with SciPy. Readers will learn how to provide solutions based on SciPy to easily implement statistical analysis and data mining along with a plethora of state-of-the-art research problems.
About the Author: Francisco J. Blanco-Silva is a celebrated applied mathematician, programmer, teacher & blogger with great experience in scientific computing. After obtaining formal training as an applied mathematician at Purdue University, he went on to become a teaching faculty in the Department of Mathematics of the University of South Carolina and proprietor of a scientific consulting company called Tizona Scientific Solutions.
Learning SciPy for Numerical and Scientific Computing starts off with teaching the readers about the basic of SciPy with relevant examples & then dives into advances applications. The book is very tactfully broken down into various branches of numerical mathematics across various application possibilities such as numerical analysis, linear algebra, statistics, signal processing, and computational geometry to name a few.
The book uncovers secrets to some of the most critical mathematical and scientific computing problems that will play an instrumental role in supporting the readers’ research. The book will teach readers how to quickly and efficiently use different modules and routines from the SciPy library to cover the vast scope of numerical mathematics with its simple practical approach that's easy to follow.
The book consists of the following chapters:
Chapter 1: Introduction to SciPy
Chapter 2: Top-level SciPy
Chapter 3: SciPy for Linear Algebra
Chapter 4: SciPy for Numerical Analysis
Chapter 5: SciPy for Signal Processing
Chapter 6: SciPy for Data Mining
Chapter 7: SciPy for Computational Geometry
Chapter 8: Interaction with Other Languages
Programmers and scientists who have basic Python knowledge and would like to work on scientific and numerical computations with SciPy will find this book to be of great help. For more details, please visit the book page at http://www.packtpub.com/learning-scipy-for-numerical-and-scientific-computing/book
|Learning SciPy for Numerical and Scientific Computing|
|A step-by-step practical tutorial with plenty of examples on research-based problems from various areas of science, that prove how simple, yet effective, it is to provide solutions based on SciPy.
For more information, please visit: http://www.packtpub.com/learning-scipy-for-numerical-and-scientific-computing/book