Numerical Python : scientific computing and data science applications with Numpy, SciPy and Matplotlib
Learn how to leverage the scientific computing and data analysis capabilities of Python, its standard library, and popular open-source numerical Python packages like NumPy, SymPy, SciPy, matplotlib, and more. This book demonstrates how to work with mathematical modeling and solve problems with numer...
保存先:
| 第一著者: | |
|---|---|
| フォーマット: | Livre papier |
| 言語: | Anglais |
| 出版事項: |
Berkeley, CA :
Apress
C 2024.
|
| 版: | Third edition. |
| Autres localisations: | Voir dans le Sudoc |
目次:
- 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
- Appendix: Installation