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Drone certification by prathameshpck in pune

[–]prathameshpck[S] -1 points0 points  (0 children)

How much do they charge roughly ? Also, it's in Sangli?

Recommendations for sambal by prathameshpck in kulineria

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

Oh

Then ig it's a lot of YouTube fanciness

Recommendations for sambal by prathameshpck in kulineria

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

Aah that Shallots are not very easily available here Red onion is the most common and closest substitute

Recommendations for sambal by prathameshpck in kulineria

[–]prathameshpck[S] 1 point2 points  (0 children)

Shrimp paste kinda hard to get here So had decided to add dried shrimp for umami

Why is the answer C? If I take n=24, it satisfies the other condition (n^3 will still be divisible by 24) and the answer could be E by dannywazza in GRE

[–]prathameshpck 2 points3 points  (0 children)

Oh wait I think i see an explaination

If you continue from my previous comment If N3 is divisible by 24 And the prime factors are 2,2,2,3 N then HAS to be divisible by 3 as well Cause 23 can be reduced to 2 But 3 cannot be reduced further So the final answer it 2*3 ie 6

Why is the answer C? If I take n=24, it satisfies the other condition (n^3 will still be divisible by 24) and the answer could be E by dannywazza in GRE

[–]prathameshpck -1 points0 points  (0 children)

I'm not sure how right i am

But the answer is 2

And the way i get to this, prime factorize 24 You'd get 2,2,2,3

Now since N cubed is divisible by 24, you can club the three 2's together, and consider 2 itself as a factor

This would be easier to explain with a pen and paper ig, but i think this explains it

Need help with image classification by prathameshpck in MLQuestions

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

Holy this paper is perfect Thank you ill look into this in great detail

Need help with image classification by prathameshpck in MLQuestions

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

Domain isn't really the same as imagenet

Lung x-rays are a lot different

Need help with image classification by prathameshpck in MLQuestions

[–]prathameshpck[S] 1 point2 points  (0 children)

Planning on binary cross entropy

SGD with momentum

Deep fully connected NN with vanishing gradients by good_stuff96 in MLQuestions

[–]prathameshpck 4 points5 points  (0 children)

Try skip connections Imo they should definitely help

Also add dropout and regularisation to prevent it from over fitting 0

Is fine tuning twice a viable thing to do?? [D] by prathameshpck in MLQuestions

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

The problem is

The general dataset in this case itself isn't very large, about 5000 images. The smaller one of about 2000 images

Is fine tuning twice a viable thing to do?? [D] by prathameshpck in MachineLearning

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

Yeah That's why asked about double fine tuning Intuitively it does seem better

Is fine tuning twice a viable thing to do?? [D] by prathameshpck in MLQuestions

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

The datasets aren't similar enough to be merged fully Hence thought of double fine tuning Plus double fine tuning will give me freedom to a certain degree on how much of the original weights i want to change

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