Hello,



More of my philosophy about artificial intelligence and about non-linear regression..

I am a white arab from Morocco, and i think i am smart since i have also invented many scalable algorithms and algorithms..


I think i am really smart, and i will talk to you more about my
interesting software project for mathematics, so my new software project
uses artificial intelligence to implement a generalized way with
artificial intelligence using the software that permit to solve the
non-linear "multiple" regression, and it is much more powerful than Levenberg–Marquardt algorithm , since i am implementing a smart
algorithm using artificial intelligence that permits to avoid premature convergence, and it is also one of the most important thing, and also
it will be much more scalable using multicores so that to search with artificial intelligence much faster the global optimum, so i am
doing it this way to be really professional and i will give you a
tutorial that explains my algorithms that uses artificial intelligence
so that you learn from them.

And read my previous thoughts:

More of my philosophy about non-linear regression and more..

I think i am really smart, and i have just finished quickly the software implementation of Levenberg–Marquardt algorithm and of the simplex
algorithm to solve non-linear least squares problems, but i have also
just implemented the PSO and genetic algorithm that permit to solve
non-linear least squares problems, and i will soon implement a
generalized way with artificial intelligence using the software that
permit to solve the non-linear "multiple" regression, but i have also
noticed that in mathematics you have to take care of the variability of
the y in non-linear least squares problems so that to approximate, also
the Levenberg–Marquardt algorithm (LMA or just LM) that i have just implemented , also known as the damped least-squares (DLS) method, is
used to solve non-linear least squares problems. These minimization
problems arise especially in least squares curve fitting. The Levenberg–Marquardt algorithm is used in many software applications for solving generic curve-fitting problems. The Levenberg–Marquardt
algorithm was found to be an efficient, fast and robust method which
also has a good global convergence property. For these reasons, It has
been incorporated into many good commercial packages performing
non-linear regression. But my way of implementing the non-linear
"multiple" regression in the software will be much more powerful than Levenberg–Marquardt algorithm, and of course i will share with you many
parts of my software project,
so stay tuned !


Thank you,
Amine Moulay Ramdane.

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