DigThatData

DigThatData t1_iue7pne wrote

Reply to comment by jellyfishwhisperer in [D] DL Practitioners, Do You Use Layer Visualization Tools s.a GradCam in Your Process? by DisWastingMyTime

very thought provoking stuff! I wonder if maybe an alternative interpretation of these observations might be something along the lines of deep image prior, i.e. maybe randomly initialized deep architectures are capable of performing edge detection just by virtue of how the gradient responds to the stacked operators?

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DigThatData t1_iu4rr8y wrote

Reply to [D] DL Practitioners, Do You Use Layer Visualization Tools s.a GradCam in Your Process? by DisWastingMyTime

sometimes, usually more likely to bust something like this out if I have a specific need than it being part of my general process. simpler metrics like gradient magnitude often get the job done well enough.

in any event, it sounds like you're interested in the tooling space so here are a few projects I think are interesting, regardless of whether or not I use them myself:

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DigThatData t1_itqbww4 wrote

Reply to Combining image and text embedding [P] by External_Oven_6379

CLIP is definitely what you want here, and it's unclear to me why you are so convinced that a categorical text representation is an important feature considering you're planning on projecting it to a dense text embedding anyway.

You should really learn about CLIP or at least survey the state of multi-modal representation learning before committing to your current layout.

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DigThatData t1_it8hvbj wrote

Reply to comment by respeckKnuckles in [D] Accurate blogs on machine learning? by likeamanyfacedgod

each point on the curve represents a decision threshold. given a particular decision threshold, your model will classify points a certain way. as you increment the threshold, it will hit the score of one or more observations, creating a step function as observations are moved from one bin to another as the decision threshold moves across their score.

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DigThatData t1_it59gaq wrote

Reply to [D] Is it worth paying a data sourcing company to crowdsource a bespoke dataset? by quantifiedvagabond

it depends on the data. considering the kind of data your working with is one of the least mature media in the analytics industry (video), it might be both significantly more cost effective and likely to produce a high-quality result if you buy the dataset. That said, if you were thinking of spinning up an in-house data annotation resource, this might be a good opportunity to go that route, and I'm sure the ML team wouldn't have any complaints if you gave them a persistent data generating resource like that.

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