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...is a collective term for characteristics that the two institutions share.
·-- PUBLISHER -----·> Packt Publishing
·-- LECTURESHIP ---·> Numerical and Scientific Computing with SciPy
·-- LECTURE DATE --·> 05-2017
03-2017 {Published}
·-- PERIOD in HRS--·> 03+
·-- SCALE ---------·> 21x50mb
·-- LECTURE LINK --·> https://goo.gl/jpbMpY
The SciPy Stack is a collection of Open-Source Python libraries finding
their application in many areas of technical and scientific computing.
It builds on the capabilities of the NumPy array object for faster
computations, and contains modules and libraries for linear algebra,
signal and image processing, visualization, and much more. Accordingly,
gaining a solid working knowledge on some of the basic functionality of
the SciPy Stack to solve mathematical models numerically is clearly the
first step before one can start using it to tackle large-scale
computational projects either in the industry or in the academic world.
This practical course begins with an introduction to the Python SciPy
Stack and a coverage of its basic usage cases. You will then delve right
into the different functionalities offered by the main modules
comprising the SciPy Stack (Numpy, Scipy, and Matplotlib) and see the
basics on how they can be implemented in real-life scenarios. You will
see how you can make the most of the algorithms in the SciPy Stack to
solve problems in linear algebra, numerical analysis, visualization, and
much more, including some practical examples drawn from the field of
Machine Learning. By the end of this course, you will have all the
knowledge you need to take your understanding of the SciPy Stack to a
new level altogether, and tackle the trickiest problems in numerical and
scientific computational programming with ease and confidence.