Further Reading

 Here's a list of 20 recommended books for further reading in applied mathematics:

1. "Numerical Recipes: The Art of Scientific Computing" by William H. Press, Saul A. Teukolsky, William T. Vetterling, and Brian P. Flannery

2. "Introduction to Algorithms" by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein

3. "Partial Differential Equations for Scientists and Engineers" by Stanley J. Farlow

4. "Introduction to Probability" by Joseph K. Blitzstein and Jessica Hwang

5. "Stochastic Processes" by Sheldon M. Ross

6. "Linear Algebra and Its Applications" by Gilbert Strang

7. "An Introduction to Mathematical Modeling" by Edward A. Bender and Suzanne C. Brenner

8. "Mathematical Methods for Physics and Engineering: A Comprehensive Guide" by K. F. Riley, M. P. Hobson, and S. J. Bence

9. "Optimization by Vector Space Methods" by David G. Luenberger

10. "Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering" by Steven H. Strogatz

11. "Convex Optimization" by Stephen Boyd and Lieven Vandenberghe

12. "Numerical Optimization" by Jorge Nocedal and Stephen J. Wright

13. "A First Course in Optimization Theory" by Rangarajan K. Sundaram

14. "An Introduction to Partial Differential Equations" by Y. Pinchover and J. Rubinstein

15. "Applied Differential Equations" by Vladimir A. Dobrushkin

16. "Introduction to Operations Research" by Frederick S. Hillier and Gerald J. Lieberman

17. "Game Theory: An Introduction" by Steven Tadelis

18. "An Introduction to Statistical Learning: with Applications in R" by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani

19. "Introduction to Time Series Analysis and Forecasting" by Douglas C. Montgomery, Cheryl L. Jennings, and Murat Kulahci

20. "Introduction to Mathematical Control Theory" by Lawrence Markus

These books cover a broad range of topics in applied mathematics, including numerical methods, probability, optimization, differential equations, and more.