NumPy: Scientific Computing

This lecture introduces NumPy, a Python library essential for scientific computing, discussing its advantages over other historically used languages like Fortran, C, C++, and Matlab. It emphasizes the importance of optimizing both computation time and memory usage in scientific calculations, highlighting the need for efficient coding practices. The lecture also explores different levels of programming languages, from low-level Assembly to high-level interpreted languages like Python, explaining how NumPy, written in C, C++, and Fortran, bridges the gap between high-level and low-level languages to provide optimized performance for scientific computations.