Ayush@TensorThrottleX
Day 131: Data Science Journey
-> Loss Functions: MSE for regression
-> Gradient: ∂aL/∂θ_j = (1/n) Σ[(f(θ, x_i) - y_i) * ∂f/∂θ_j]
-> Backprop: Chain rule across layers; ∇L via forward act & backward grad
->Learning Rate: Controls step size in GD
#ML #DataScience #LearningRate
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