
Linear algebra has emerged as a cornerstone of data science, fueling advancements in machine learning, neural networks, and data transformation. This mathematical discipline is not merely theoretical but provides tangible solutions for processing and interpreting expansive datasets that power today’s technology-driven world. Matrix operations, vector spaces, and dimensionality reduction techniques are crucial to the implementation and effectiveness of data science










