Jupyter Notebooks for Numerical Analysis

Covers the basics of numerical analysis and computational methods using Python, focusing on algorithms and practical applications in mathematics.

Covers the basics of scientific computing with Python, focusing on programming, algorithms, and numerical methods.

Discusses the bisection method for solving nonlinear equations and its implementation using Python with NumPy and Matplotlib.

Covers root-finding methods, focusing on the bisection and secant techniques, their implementations, and comparisons of their convergence rates.

Covers classical mechanics, molecular dynamics, integrators, constant-temperature simulations, and melting point calculations for aluminum.