Numerical Python Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib

Numerical Python Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib / by Robert Johansson.

Leverage the numerical and mathematical modules in Python and its standard library as well as popular open source numerical Python packages like NumPy, SciPy, FiPy, matplotlib and more. This fully revised edition, updated with the latest details of each package and changes to Jupyter projects, demon...

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Bibliographic Details
Main Author: Johansson, Robert (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Berkeley, CA : Apress : Imprint: Apress, 2019.
Edition:2nd ed. 2019.
Series:Springer eBook Collection.
Subjects:
Python (Computer program language).
Computer software.
Big data.
Artificial intelligence.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • 1. Introduction to Computing with Python
  • 2. Vectors, Matrices and Multidimensional Arrays
  • 3. Symbolic Computing
  • 4. Plotting and Visualization
  • 5. Equation Solving
  • 6. Optimization
  • 7. Interpolation
  • 8. Integration
  • 9. Ordinary Differential Equations
  • 10. Sparse Matrices and Graphs
  • 11. Partial Differential Equations
  • 12. Data Processing and Analysis
  • 13. Statistics
  • 14. Statistical Modeling
  • 15. Machine Learning
  • 16. Bayesian Statistics
  • 17. Signal and Image Processing
  • 18. Data Input and Output
  • 19. Code Optimization.

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