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Gradient descent is an optimization algorithm used to minimize some function by iteratively moving in the direction of steepest descent as defined by the negative of the gradient.

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Currently finishing Joy of Vex, Entagma videos, Vex for Artist just to build the necessary knowledge to watch these. Super excited, I will pre-buy shortly. Thank you for such an incredible series. 

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Hello Yunus, this course looks outstanding, thanks for sharing!

How did you combine the Scene View with Network View (when you manage the creation of nodes on top of the camera view)?

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2 hours ago, kiryha said:

Hello Yunus, this course looks outstanding, thanks for sharing!

How did you combine the Scene View with Network View (when you manage the creation of nodes on top of the camera view)?

Thanks a lot Kiryha!

I achieved the overlay network editor by writing a lot of Python Qt code :)

https://gumroad.com/animatrixx#Igugf

It doesn't seem to work on mac/iOS though due to some weird Qt bug.

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On 8/17/2020 at 12:47 PM, NoaX said:

Currently finishing Joy of Vex, Entagma videos, Vex for Artist just to build the necessary knowledge to watch these. Super excited, I will pre-buy shortly. Thank you for such an incredible series. 

Same here. trying to prepare my self for this one! Looks so good!!!!

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Thanks a lot guys!

On 2020-08-20 at 8:39 PM, cudarsjanis said:

Same here. trying to prepare my self for this one! Looks so good!!!!

You can always interleave with other content :) Even though the course is advanced, there is still a progression of complexity within the course. So starting with basic elements, it gradually ramps up in complexity and ends with highly technical topics.

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We have implemented gradient ascent and descent on planar geometry, much like a terrain where we used the gradient of the height.

For an arbitrary geometry, what can we use as the cost attribute? One thing we can use is depth.

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Now that we know about gradients, there is another concept that's related to them that can be acquired quite easily, and that concept is contour lines.

A contour line (also isoline) of a function of two variables is a curve along which the function has a constant value, so that the curve joins points of equal value. There are very interesting relationships between the gradients and the contour lines.

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We have already seen how to apply gradient ascent, descent and contour lines to heightfield like planar geometry. The same concept can be applied to heightfields.

Because heightfields are volumes, getting the gradient is very easy by using the volumegradient function. The normal of a heightfield is (0, 1, 0) if the heightfield is an XZ volume, meaning facing up. Getting the cross product of both of these vectors will give you the contour lines.

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Subdivision surfaces are piecewise parametric surfaces defined over meshes of arbitrary topology.

It's an algorithm that maps from a surface to another more refined surface, where the surface is described as a set of points and a set of polygons with vertices at those points. The resulting surface will always consist of a mesh of quadrilaterals.

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