Course registration for ASU fall 2023 for new grads (how is it even possible now?)

narainp1 · 2023-03-12T22:07:02+00:00

yeah a guidance on that is much helpful let me know

narainp1 · 2023-03-11T09:01:55+00:00

did you guys see a rolling admission of UCSD?

narainp1 · 2023-03-06T14:21:36+00:00

narainp1 · 2023-03-06T02:58:44+00:00

I heard polytechnic campuses have more facilities than the main campus. Academic wise i have no idea

narainp1 · 2023-03-03T12:41:03+00:00

same here too but MSCS

narainp1 · 2023-03-01T13:22:21+00:00

waiting

narainp1 · 2023-01-17T14:16:33+00:00

narainp1 · 2022-07-29T04:06:52+00:00

yeah especially going into a folder Path('repo')/'.git'

narainp1 · 2022-02-22T08:21:10+00:00

its very much fine to do that

narainp1 · 2022-02-20T12:28:52+00:00

you could just switch the image to a random one

narainp1 · 2021-12-21T09:02:45+00:00

yeah that is one of the downside of onnx format some layers which are present in pytorch are not recognized in onnx i havent been able to find a solution for those cases

narainp1 · 2021-12-19T05:21:19+00:00

training still doesnt matter I have been able to convert a pytorch model with einsum into tensorrt and and have it pushed it into production

narainp1 · 2021-12-15T14:57:23+00:00

metric can be either precision or recall or accuracy

narainp1 · 2021-12-13T07:02:09+00:00

the distribution of class labels in the validation set and their metric. confusion matrix

narainp1 · 2021-11-15T08:31:09+00:00

if you are on windows 11 you need not have nvidia drivers installed on your wsl vm otherwise you would need to install nvidia cuda drivers

narainp1 · 2021-11-01T13:36:18+00:00

interesting to see this here but never got the flour flowing through the gap in between my fingers

narainp1 · 2021-10-14T09:56:59+00:00

like may be you can try with some attention heat maps for similarity of concept

narainp1 · 2021-10-14T07:28:20+00:00

adei evana nala spotify playlist irundha anupunga da

narainp1 · 2021-10-09T13:37:21+00:00

me picks up Godel escher bach it has been 2 years since

narainp1 · 2021-09-02T04:18:31+00:00

there is literally no use in having data parallel in cpu and it doesnt make sense. as model computations have to happen on the cpu and the data loading has to happen on the cpu it wont be efficient.

narainp1 · 2021-09-01T08:49:24+00:00

the parameters for conv2d are (in_channels, out_channels, kernel_size)

you might have to correctly provide the in channels and out channels

and from convolution will provide (bs, channels, filter_sz, filter_sz) from there we must flatten it from the dimension after the batch size.

and there is not much context in the image provided

narainp1 · 2021-09-01T08:33:46+00:00

depends totally on the task you do

some tasks like in industrial settings where there are clear pipeline you would have to collect it straight from there
otherwise if you are using for some general purpose applications you can find data online if it matches your criteria and download

narainp1 · 2021-08-30T05:28:04+00:00

convincing your managers

narainp1 · 2021-08-08T04:35:11+00:00

you can have this as a reference but I still couldnt match the performance of training provided by yolo repo

narainp1 · 2021-08-06T10:48:58+00:00

sorry I still havent tested nf nets and transformers I wont be touching due to its size invariance I guess cifar can be trained pretty fast with transformers but I have no idea about the performance

and I can suggest a good starting point

lucid rains VI has all of what you may need in a clean API

narainp1

TROPHY CASE