30 Comments
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Rocco Jarman's avatar

Outstanding resource. Thanks!

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sciencetalks's avatar

No amount of words can describe how grateful I am for you to have compiled a stunning resource such as this one. Thank you very much for all of your time and effort! Will definitely be sharing with friends. Can't wait to read more, subscribed. :))

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Sani Nassif's avatar

Small typo in figure. c^2 = a^2 + b^2, not the square root of ...

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Tivadar Danka's avatar

Thanks, you are correct!

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Adriatic's avatar

This article is written extremely well - a very difficult task, as it represents complex math constructs using everyday’s english language. This approach is current methodology in writing books on state of the art quantum field theory.

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Vladimir Shitov's avatar

Thank you, that’s a wonderful article! Small typo:

> Take a small step in the direction of the gradient to arrive at the point x₁. (The step size is called the learning rate.)

The steps should be taken in the opposite direction :)

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Tivadar Danka's avatar

Thanks, I'll fix this ASAP!

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Vladimir Shitov's avatar

It’s actually pretty fun to follow the gradient once and see how the loss diverges.

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Saurabh Dalvi's avatar

Much needed thanks

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Kovats William's avatar

Is there a typo in your formula:

<ax+y,z> =a<x,z> + <x,y> = <y,z> ?

I would have thought <ax+y,z>= a<x,z> + <y,z>

but I might just not be understanding something.

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Alberto Sasso's avatar

I do agree, that should describe the linearity feature.

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Neha Vari's avatar

A small correction, if you could do in Pythagoras Theorem diagram, it should be c2=a2+b2....

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gr1.61803's avatar

This is good.

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Benjamin Nelson's avatar

These are so few and far between the endless stream of nonsensical pseudo-philosophical and quasi-intellectual detritus that continue to muddy the waters around understanding how these systems are made, what's meaningful about them, and why they work the way they do. Unlike this brilliant work, those failures continue to isolate experts from the demos and more so, the further along the cutting edge we move from traditional intelligence system architectures. This is an amazingly comprehensive and wonderfully easy to understand educational resource. If I wasn't a scientist, I'd have money to offer you in kind for this amazing learning tool. Hope we get to see a following work that delves further into increasingly complex mathematics, self-referential architectures, and SOTA implementations like dimensionality reduction, analogue cognitive field mechanics, markovian dynamics, and more. A neverending landscape of possiblity awaits those with the moxy to explore and works like this equip those brave adventurers with the tools needed to navigate these boundless paths into consciousness within and without. Well done.

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Luis Rodriguez's avatar

🙌🏻🙌🏻🙌🏻

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Will Smith's avatar

Thank-you very much. This was helpful to me, to help me understand how our system works.

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bluematrix's avatar

Great work.

Just another hint: in the diagram explaining vector addition, you may want to connect the base of vector y to the point of vector x, to visualize they add up to x+y.

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Dr. U V's avatar

Looks like a great primer for novice like me in machine learning..My forte is number theory and developing math puzzles and games

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GREGORY LEWIS YOCK's avatar

I have wanted such a tool for learning for ages I cannot thank you enough and thank you to all of the contributors in the comments

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Steve Eisenberg's avatar

Thanks for the info. I'm eager to learn, but have never been strong with advanced math. Is there any way around it using tools to compensate?

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