Linear Algebra is the engine of AI. Neural Networks are essentially giant matrix multiplications. NumPy provides a specialized `linalg` module that makes this complex math incredibly fast and accessible.
1Vectors and Dot Products
A 1D NumPy array is a vector. The dot product—the sum of the products of corresponding entries—is a foundational operation for calculating network weights and similarity scores between datasets.
2Matrix Multiplication
Unlike element-wise math, matrix multiplication requires strict dimension alignment. NumPy uses the @ operator (or np.matmul()) to perform these operations, which are the backbone of almost all modern AI algorithms.
