Outline:
- Referensi/Materi
- Referensi Video
- Code/Module
- Forum Diskusi
Referensi/Materi
- https://www.cs.princeton.edu/courses/archive/fall09/cos323/lectures/cos323_s06_lecture03_optimization.ppt
- https://eclass.aueb.gr/modules/document/file.php/STAT263/W.%20John%20Braun%2C%20Duncan%20J.%20Murdoch%20-%20A%20First%20Course%20in%20Statistical%20Programming%20with%20R%20%282016%2C%20Cambridge%29.pdf
- http://www.mee.tcd.ie/~sigmedia/pmwiki/uploads/Main.Tutorials/Introduction_to_Numerical_Optimization.pdf
- Materi Bahasa Indonesia
Referensi Video
- https://www.youtube.com/watch?v=ms3aKKW_iRc
- https://www.youtube.com/watch?v=hTslJ9A3peA
- https://www.youtube.com/watch?v=tnOOiSjTI8I&list=PL6EA0722B99332589&index=4
Open Code in Google Colaboratory
Jangan lupa kolom komentar bukan untuk berdiskusi/bertanya, untuk keperluan tersebut silahkan klik tautan untuk menuju Forum terkait modul ini.
What’s Next?
Referensi:
- Johansson, R. (2018). Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib. Apress.
- John H. Mathews, Numerical Methods for Mathematics, Prentice Hall, 1992 [Refernsi Utama]
- Heath, M. T. (2018). Scientific computing: an introductory survey (Vol. 80). SIAM.
- Conte, S. D., u0026amp; De Boor, C. (2017). Elementary numerical analysis: an algorithmic approach (Vol. 78). SIAM.
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