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Numerical Python = a practical techn...

Johansson, Robert.

Numerical Python = a practical techniques approach for industry /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Numerical Python/ by Robert Johansson.
其他題名:	a practical techniques approach for industry /
作者:	Johansson, Robert.
出版者:	Berkeley, CA :Apress : : 2015.,
面頁冊數:	xxii, 487 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
標題:	Mathematical Software. -
電子資源:	http://dx.doi.org/10.1007/978-1-4842-0553-2
ISBN:	9781484205532

Numerical Python = a practical techniques approach for industry /
Johansson, Robert.

Numerical Pythona practical techniques approach for industry /[electronic resource] :by Robert Johansson. - Berkeley, CA :Apress :2015. - xxii, 487 p. :ill., digital ;24 cm.

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 -- 20. Appendix: Installation.

ISBN: 9781484205532

Standard No.: 10.1007/978-1-4842-0553-2doiSubjects--Topical Terms:

672446
Mathematical Software.

LC Class. No.: QA76.73.P98

Dewey Class. No.: 005.133

Numerical Python = a practical techniques approach for industry /
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505 0 $a 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 -- 20. Appendix: Installation.
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