Linear Algebra in NumPy: Math With Code

Ten posts. Vectors. Matrices. Dot products. Matrix multiplication. Derivatives. Gradient descent. Statistics. Probability. Normal distributions. Every single concept explained. Zero of them actually running together in one place. Until now. This post is different from every other in Phase 2. No new concepts. No theory. Just code. Everything you learned over the last ten posts wired together in NumPy, running on your machine, producing real output. Think of it as your Phase 2 exam. Not a test you