NumPy practice notebook covering array operations, indexing, slicing, broadcasting, stacking, and basic linear algebra. Focuses on vectorization and efficient numerical computing for data science and ML. Demonstrates strong fundamentals and hands-on learning in NumPy for real-world analytical tasks.