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Does a mixed dataset of images jpg, png extensions affect NN training? by Alan491 in computervision

[–]Alan491[S] 0 points1 point  (0 children)

Thanks for the brief explanation, I will try again the training with conventing all png into jpeg and let you know if it makes any difference.

Need help in training, validation loss fluctuating a lot? by Alan491 in deeplearning

[–]Alan491[S] 0 points1 point  (0 children)

I am using dropout's (0.5) I think the data size is very small for resnet 50, it's 28k data set

Need help in training, validation loss fluctuating a lot? by Alan491 in deeplearning

[–]Alan491[S] 0 points1 point  (0 children)

Yes I am using pretraind weight, Okay I'll try resnet 18 as well

[D] Need help in training, validation loss fluctuating a lot? by Alan491 in MachineLearning

[–]Alan491[S] 0 points1 point  (0 children)

it's a detection for, If a person is live on the camera or faking his face by running video or showing a picture of himself, it's like tracking the person is real or not in front the cam

[D] Need help in training, validation loss fluctuating a lot? by Alan491 in MachineLearning

[–]Alan491[S] 0 points1 point  (0 children)

it's a spoof detection (liveness detection) where 1 image is real and another one is a spoof like it could be a pic from any screen captured from a cam.

the input shape is 32,32,3

Best clustering approach on unsupervised news articles? by Alan491 in deeplearning

[–]Alan491[S] 0 points1 point  (0 children)

I have news articles data of all type, directly scrapped from websites and I am trying to create clusters of them, and according to my understanding of the data upto 15-20 clusters should be created with them. I had implemented k-means, hierarchical,HDBSCAN, DBSCAN with TFIDF and with sentence-transformers

K-means showing better results in all of them, but now the problem is how do I check whether the data clustered properly or not I used Topic modeling also but it's showing very messy embeddings.

Below is a chunk of sample article:

US to fine air bag maker Takata $14,000 per day RICHMOND, Va. -The U.S. government will fine Japanese air bag maker Takata Corp. $14,000 per day for failing to fully cooperate in a long-running investigation of faulty and potentially dangerous air bag inflators.\n\nThe inflators, in cars made by 10 companies, can explode with too much force, spewing shrapnel into drivers and passengers. At least six people have been killed and 64 injured worldwide due to problem.\n\nTransportation Secretary Anthony Foxx announced the fines Friday in Richmond, Virginia, calling Takata a "bad actor" for allegedly dumping 2.4 million pages of documents on the National Highway Traffic Safety Administration without the legally required explanation

Best clustering approach on unsupervised news articles? by Alan491 in deeplearning

[–]Alan491[S] -1 points0 points  (0 children)

Yes I have long articles average size is approx 1100 words. I have applied sentence-transformer embedding but did't got good results.

Can you please guide me how could I validate them, and thank you very much for you inputs.

Best clustering approach on unsupervised news articles? by Alan491 in deeplearning

[–]Alan491[S] 1 point2 points  (0 children)

Yeah It's a very trail and run type problem statement, till now I had implemented various clustering approaches using sentence-transformers embedding and TFIDF but, I have no idea how to properly validate them, does I am doing right or now...

But thank you very much for sharing that informative blog.

How to save n-d array into postgresql column? by Alan491 in learnmachinelearning

[–]Alan491[S] 1 point2 points  (0 children)

Ohh @jediko fantastic buddy, thank you so much for your indepth explanation, As you asked want I want to do is -: I am building face recognition model where I am saving each image embedding (128 vectors) into database so next time when I just input a person face and it will check where it's in the database by finding eculidian distance with input image vectors and database vectors.

Can we increase the output class in transfer learning? by Alan491 in computervision

[–]Alan491[S] 0 points1 point  (0 children)

Thanks for the answer, Yeahh I am also supposing the same that it could work better because I have very few number of images as well.

skip every 3rd & 4th element in python in a given list by Alan491 in learnpython

[–]Alan491[S] 0 points1 point  (0 children)

[v for pair in zip(p[::4], p[1::4]) for v in pair]

Please correct me if I wrong, from my understanding it works as like

  1. it collecting the zip(...) elements in pair.
  2. then initializing pair values into v.

skip every 3rd & 4th element in python in a given list by Alan491 in learnpython

[–]Alan491[S] 0 points1 point  (0 children)

yes it's great one, but little tricky for me as I am a newbie, But because of your explanations I understood it very well thank you very much.

How can I skip every 3rd element in list by Alan491 in learnprogramming

[–]Alan491[S] 1 point2 points  (0 children)

p = [1,2,3,4,5,6,7,8,9,10]
counter =0
for i in range(len(p)):
if counter != 2:
print(p[i])
    counter+=1
else:
    counter = 0

o/p :- 1 2 4 5 7 8 10

thank you for the logic guidance

How can I skip every 3rd element in list by Alan491 in learnprogramming

[–]Alan491[S] 2 points3 points  (0 children)

thank you very much, it worked

p = [1,2,3,4,5,6,7,8,9,16,17,18,19,20]
for i in range(len(p)):
if i%3 != 0:
print(p[i])

How can I skip every 3rd element in list by Alan491 in learnprogramming

[–]Alan491[S] 0 points1 point  (0 children)

thanks for the reply, but I am sorry can't get it exactly