gradientdescent.jl

using Zygote
using Distributions

lm(x, m, b) = m .* x .+ b

x = rand(Uniform(-2, 2), 100)
ε = rand(Normal(0.0, 0.05), length(x))
p₀ = [-1.2, 0.05]

y = lm(x + ε, p₀...)

L2(y, x, f, p...) = sum(
    (y .- f.(x, p...)).^2.0
    )/length(x)

p = rand(length(p₀))

∇L(y, x, f, p...) = gradient(
    (p...) -> L2(y, x, f, p...),
    p...
)

η = 0.01

for epoch in 1:50_000
    p .-= η .* ∇L(y, x, lm, p...)
end

round(p[1]; digits=5)
round(p[2]; digits=5)