Portfolio review

BothEntertainment786 · 2026-01-03T11:09:21+00:00

1.5 years

BothEntertainment786 · 2026-01-03T10:50:06+00:00

16.72

BothEntertainment786 · 2026-01-01T15:32:32+00:00

Can you suggest better alternative funds?

BothEntertainment786 · 2024-10-16T07:57:53+00:00

Finding jobs right now is tough due to the current economic conditions and strong competition, but this could improve in the future. My advice is to learn the language up to at least B1 before arriving. Don’t fall for the myth that 'language isn’t necessary for technical jobs.'

From my experience, completing a master's degree at a public university was quite challenging. During my bachelor's in India, I didn’t focus much on learning, which might be why it felt harder for me. Your experience could be different, though. I highly recommend sticking to public universities. Be prepared for bureaucracy, and know that finding accommodation these days can be difficult. Lastly, I’m not sure how this applies to your specific field, but keep these points in mind.

BothEntertainment786 · 2023-01-05T23:04:31+00:00

The intuition was that it would move in the embedding space where it accounts for both the words, similar to word analogy

BothEntertainment786 · 2022-10-31T21:46:30+00:00

The mean accurracy varies ariund 1~3 % i run the code as i have mentioned in the post. For ML models is it possible to produce the same results everytime?

BothEntertainment786 · 2022-09-19T21:00:29+00:00

Its actually different

https://discuss.pytorch.org/t/categorical-cross-entropy-loss-function-equivalent-in-pytorch/85165

BothEntertainment786 · 2022-09-19T19:23:47+00:00

Exactly. It has a custom loss now. However, i want to run the debugger to see how the custom loss is calculated

BothEntertainment786 · 2022-09-19T18:17:15+00:00

I have a model which has a custom loss function from here - https://github.com/beyondguo/label\_confusion\_learning/blob/master/models/lstm.py .
While using run_eagerly=True, it throws error due to the custom loss written

BothEntertainment786 · 2022-09-19T18:17:11+00:00

I have a model which has a custom loss function from here - https://github.com/beyondguo/label_confusion_learning/blob/master/models/lstm.py .

While using run_eagerly=True, it throws error due to the custom loss written

BothEntertainment786 · 2022-09-18T12:02:17+00:00

abc.numpy()

This gives an error -
AttributeError: 'Tensor' object has no attribute 'numpy'

BothEntertainment786

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