Numerical Methods in Physics with Python

This comprehensive textbook combines Python programming, numerical methods, and physics applications to provide a practical introduction to computational physics. It covers essential techniques such as linear algebra, differential equations, optimization, interpolation, integration, Fourier transforms, machine learning, and partial differential equations, with clear explanations, derivations, and Python/NumPy code examples. Featuring over 60 complete programs, 140 new problems, and hands-on physics projects, it helps students quickly learn Python while mastering the computational tools widely used in modern physics and scientific computing.