Mastering Python Scientific Computing
- 300 pages
- 11 hours of reading
Through the use of real-life case studies and best practices of scientific computing, Mastering Python scientific computing, is a guide that identifies the fundamentals and components of scientific computing and data management. Users will have the opportunity to perform parallel and high performance computing, perform numerical computing using Numpy and SciPy, demonstrate the concepts and programming for symbolic computing using SymPy, and analyze data analysis and visualize it using pandas, matplotlib, and IPython
