terasakisatoshi

# Multiple dispatch
#https://www.juliabox.com/notebook/notebooks/tutorials/intro-to-julia/10.%20Multiple%20dispatch.ipynb

using InteractiveUtils
versioninfo()


#= 
In this script we'll explore multiple dispatch, which is as key 
feature of Julia.

terasakisatoshi

# https://www.juliabox.com/notebook/notebooks/tutorials/intro-to-julia/AutoDiff.ipynb
# Auto Diff

using InteractiveUtils
versioninfo()

# The example is the Babylonian algorithm, known to man for millenia, to compute sqrt(x)
function Babylonian(x; N = 10)
    t = (1+x)/2
    for i = 2:N # For illustration purposes, 10 iterations suffice.

terasakisatoshi

# https://www.juliabox.com/notebook/notebooks/tutorials/intro-to-julia/AutoDiff.ipynb
# Dual Number

using InteractiveUtils 
versioninfo()

struct D <: Number 
    f::Tuple{Float64,Float64}
end 

terasakisatoshi

# auto diff from scratch

"""
Reference:
https://www.juliabox.com/notebook/notebooks/tutorials/intro-to-julia/AutoDiff.ipynb
http://hplgit.github.io/primer.html/doc/pub/class/._class-readable005.html
https://docs.python.jp/3/reference/datamodel.html#object.__radd__
https://docs.python.org/3/whatsnew/3.5.html#pep-485-a-function-for-testing-approximate-equality
https://docs.python.jp/3/library/operator.html#module-operator
https://www.physicsforums.com/threads/derivative-of-f-x-to-the-power-of-g-x-and-algebra-problem.273333/

terasakisatoshi

terasakisatoshi

#=
Linear Regression using Flux.jl

pkg> add Flux#master
pkg> add Plots

Reference:
https://qiita.com/cometscome_phys/items/f58174c0dad7ecb811ed

=#

terasakisatoshi

terasakisatoshi

terasakisatoshi

terasakisatoshi