| Required or Recommended Resources |
1) Burden, R. L., & Faires, J. D. (2005). Numerical Analysis (8th ed.). Thomson.2) Bober, W., & Stevens, A. (2013). Numerical and Analytical Methods with Matlab for Electrical Engineers. CRC Press.3) Esfandiari, R. S. (2013). Numerical Methods for Engineers and Scientists4) Gilat, A., & Subramaniam, V. (2014). Numerical Methods for Engineers and Scientists.5) Stewart, D. E. (2020). Numerical Analysis – A Graduate Course. Springer.6) Fox, W. P., & West, F. (2025). Numerical Methods and Analysis with Mathematical Modelling. CRC Press.7) Altaç, Z. (2025). Numerical Methods for Scientists and Engineers. CRC Press.8) Bakr, M. (2013). Nonlinear Optimization in Electrical Engineering with Applications in Matlab. IET.9) Arora, J. S. (2017). Introduction to Optimum Design (4th ed.). Elsevier.10) Rao, S. S. (2020). Engineering Optimization (5th ed.). Wiley.11) Corriou, J. P. (2021). Numerical Methods and Optimization. Springer.12) Stanimirovic, I. (2022). Advances in Optimization and Linear Programming. Taylor and Francis.13) Monteiro, & Meza. (2026). A Practical Guide to Optimization in Engineering and Data Science. Springer.14) Burkov, A. (2019). The Hundred-Page Machine Learning Book.15) Deisenroth, M. P., Faisal, A. A., & Ong, C. S. (2020). Mathematics for Machine Learning. Cambridge University Press.16) Sridhar, S., & Vijayalakshmi, M. (2021). Machine Learning. Oxford Publishing.17) Nelson, H. (2023). Essential Math for AI. O'Reilly.18) Bohn, B., Griebel, M., & Rieger, C. (2024). Algorithmic Mathematics in Machine Learning. SIAM.19) Serrano, L. G. (2025). Grokking Machine Learning. Manning. |