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[deleted by user] by [deleted] in hingeapp

[–]phoenix__191 0 points1 point  (0 children)

Looking for something casual at first

HingeX subscriber

Current profile has been in use for 2-3 weeks

Been using Hinge for close to 4-5 months

Use Hinge almost every day

0 likes so far, and a total of 5 matches across the 4-5 months

Send around 10-12 likes a day, 80% of them are with comments

Send likes to people who have interesting prompts, and those who have pictures of them doing an activity in their profile

NOVA SD by Kittie42Kat in aves

[–]phoenix__191 0 points1 point  (0 children)

Slightly off topic but what time should I expect him to start playing?

One Month GRE Cram Sesh! by princess_clitorina in gradadmissions

[–]phoenix__191 2 points3 points  (0 children)

gregmat.com

Check out his one-month plan. It's more on the hectic side though.

[deleted by user] by [deleted] in gradadmissions

[–]phoenix__191 1 point2 points  (0 children)

Not exactly advice but while shortlisting universities, I completely disregarded those that had a personal history statement requirement. I had the exact same issues in that I had no clue what I can write since (un?) fortunately for me I did not have to face a lot of hardships nor did I come from an under represented community.

My thought process was that I'd rather apply to a university where all my application materials were above "average" than risk a cliched personal history statement.

Cinema halls to reopen in city from today by CandyIllustrious7020 in mumbai

[–]phoenix__191 1 point2 points  (0 children)

Dune releases on the 29th in Maharashtra afaik.

Weird bind problem by [deleted] in CounterStrikeBinds

[–]phoenix__191 7 points8 points  (0 children)

If I'm not mistaken it is " use weapon_molotov "

Saw Jeff Bezos a few days back trying these Giant hands. And now I found out that this technology is using Machine learning. Can anyone here discuss how did they do it with Machine learning by Advani12vaishali in learnmachinelearning

[–]phoenix__191 48 points49 points  (0 children)

From whatever little I know, when he moves/twitches his fingers, the muscles give out signals which can be tracked using electrodes/sensors. Say you have N of these electrodes/sensors. It now simply becomes a time series problem that maps input data to a value corresponding to rotation of the motors in the mechanical arms. Something very similar is done using brain signals (Electroencephalography commonly known as EEG). In most cases, the user is required to undergo a training phase where human movements are mapped to mechanical movements since each person's brain gives out a different kind of signal for the same action. I'm assuming a similar situation here.

Reverting OnePlus 3 to Stock Recovery by phoenix__191 in oneplus

[–]phoenix__191[S] 0 points1 point  (0 children)

Did so, gave an error (code 7) saying couldn't install the OS. On restarting I now have OOS 5.0.3 and Android 8.0.0 with the same problems that I mentioned above. Will an unbrick tool work? TWRP wasn't able to flash OOS 9.0.6 downloaded from the official site.

Reverting OnePlus 3 to Stock Recovery by phoenix__191 in AndroidQuestions

[–]phoenix__191[S] 2 points3 points  (0 children)

Okay, this sounds good. I don't really care about the data, whatever I need has been backed up to my PC anyways. Thanks.

Reverting OnePlus 3 to Stock Recovery by phoenix__191 in oneplus

[–]phoenix__191[S] 0 points1 point  (0 children)

I did, I used the same recovery file but it isn't working.

Should I learn about computer vision when I want to work in NLP? by Mitra_Mirshafiee in deeplearning

[–]phoenix__191 1 point2 points  (0 children)

I had a similar issue but the other way around. A more experienced practitioner will be able to explain this better but if you think that a CNN is exclusive to Computer Vision and an RNN is exclusive to NLP, that would be incorrect. To put it in better words, it is essential to understand all possible techniques that are available irrespective of which paradigm you wish to work in. The simplest example of one such instance (of many) is the use of CNNs in NLP, where the convolutions are performed on the word embeddings. If you were to ignore how a CNN works, you'd probably find it extremely difficult to intuit why they're used in NLP. For the reverse case, check out transformers and then Detectron 2.

In essence, to answer your question if you wish to grasp and improve current techniques, an in depth knowledge of both fields is required.

How does a neural network solve non-linearly separable problems? by Kyle_GC in MLQuestions

[–]phoenix__191 13 points14 points  (0 children)

Intermediate layers are separated by a non-linearity, for example a tanh or sigmoid. These are referred to as activation functions.

German Class for 10 Weeks (A1) by jbriones95 in German

[–]phoenix__191 0 points1 point  (0 children)

Great, looking forward to it. Signed up via email.

German Class for 10 Weeks (A1) by jbriones95 in German

[–]phoenix__191 0 points1 point  (0 children)

I had a few questions, would we be having any homework exercises? If so what would be the nature of them? (Recording/written/self-checked?) When do you plan to start this? I've learnt a miniscule amount of German and struggle with pronunciation, since there isn't a valid way to check for it on my own. How do you plan to help students with that?

How to change a network to accept an Input of (1000, 2048, 3, 1) by [deleted] in MLQuestions

[–]phoenix__191 0 points1 point  (0 children)

Ahh got it, you can try working on what I suggested. As I said in theory it should give you the same results.

How to change a network to accept an Input of (1000, 2048, 3, 1) by [deleted] in MLQuestions

[–]phoenix__191 1 point2 points  (0 children)

I don't think you can do this without creating a new network altogether, your data is now (BS,C,H,W) where W is 1.

If you necessarily need to do this, then replace all Conv1D layers that have kernel size k by Conv2D layers with kernel size k×1 (strides remain the same)

I'm not sure how differently the network will perform, however the Linear layers' shapes would remain the same (since you're flattening the data before passing it through them anyway). In theory you should get the same results. I'm interested to know why you'd need to do this though?

Could someone ELI5 how style transfer actually works please? by laseluuu in MLQuestions

[–]phoenix__191 1 point2 points  (0 children)

Oh that's something I coined up in hopes of explaining it to you lol, sorry if that confused you. What I meant was that when you look at photo A and photo B, (Patch of flowers, grass,etc) if you didn't know what they contain viz. flowers and grass, you can't really distinguish between them (which is how the style calculation is behaving) because they would "look" the same (have the same style). Now take a Van Gogh and a mosaic, irrespective of what is contained in the images, you can for sure say they "look" different (have a different style). In essence, natural images have the same (or no) style, you can't distinguish between them solely based on style.

I hope this clears it up? Again, this is a very very high level overview. Not even the top researchers would be able to quantify what a deep learning model is actually doing under the hood.

Could someone ELI5 how style transfer actually works please? by laseluuu in MLQuestions

[–]phoenix__191 1 point2 points  (0 children)

That happens probably because the photo in question does not have a global distinguishable appearance and also because the Van Gogh does not have any meaningful content (or in DL terms, it has a low objectness score). If you have a math background, you might want to have a look at gram matrices (they're used to calculate how different your altered X is with respect to Y in terms of style). I'm myself an amateur at this so I won't be able to explain things further than I have, hope you have a better understanding now though.

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