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I had never actually seen "Data Science from Scratch" - sounds like a book I should read!

Fair point about the gradient descent Vs normal equations closed form solution. I am planning on working through a few algorithms so thought it would be better to introduce gradient descent with something simple before talking about gradient boosted decision trees and Neural Networks. Also I would have to explain more complex matrix stuff like invertibility issues and linear dependance like you said.

I guess I just dodged that bullet and went for gradient descent. Maybe another post for the linear algebra fans! Thanks for reading though!




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