FUTURE FOR SCIENTIFIC COMPUTING USING PYTHON
Keywords:IPython, Matplotlib, NumPy, Python, Pandas, Scientific Computing, Sympy, SciPy
Computational science (scientific computing or scientific computation) is concerned with constructing mathematical models as well as quantitative analysis techniques and using computers to analyze as well as solve scientific problems. In practical use, it is basically the application of computer simulation as well as other forms of computation from numerical analysis and theoretical computer science to problems in different scientific disciplines. The scientific computing approach is to gain understanding, basically through the analysis of mathematical models implemented on computers. Python is frequently used for highperformance scientific applications and widely used in academia as well as scientific projects because it is easy to write and performs well. Due to its high performance nature, scientific computing in Python often utilizes external libraries like NumPy, SciPy and Matplotlib etc.
Python Scientific Lecture Notes: https://scipy-lectures.github.io/
Scientific computing tools for python: http://www.scipy.org/
SciPy library: http://www.scipy.org/scipylib/
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