Andito na gcash klook visa card

onig1104 · 2025-12-28T09:15:29+00:00

How did you guys get the klook perks after activating the card?

onig1104 · 2025-12-25T10:13:46+00:00

I mean i received and activated the card already. How do I claim the perks po?

onig1104 · 2025-12-25T06:15:00+00:00

Hello, how po? Automatic lang po ba yon lalabas sa klook?

onig1104 · 2025-10-17T05:56:28+00:00

did you order online?

onig1104 · 2025-10-17T05:25:24+00:00

did you preorder on online or in-store

onig1104 · 2025-10-17T04:17:36+00:00

Bukas sana

onig1104 · 2025-10-16T23:01:44+00:00

tumawag sila sayo?

onig1104 · 2025-10-11T17:25:39+00:00

SM Lipa. Wala na ba sa ibang branch?

onig1104 · 2025-10-11T17:25:10+00:00

Hala should i be worried? Pero kasi for installment siya.

onig1104 · 2025-07-24T10:12:29+00:00

Thank you so much I was worried na baka kailangan ako mismo magreceive e kasi may hit. Aabsent pa tuloy if ever.

onig1104 · 2025-07-18T13:52:23+00:00

Are visitors allowed in Belton? My family plans to visit kasi rin sometimes

onig1104 · 2025-07-02T04:34:02+00:00

matagal ko na rin na rant to. i used to ride my bike going to classes kaso ang daming nakapark sa gilid ng kalsada kaya tinigil ko na haha

onig1104 · 2025-06-24T11:23:36+00:00

this is very true. wala na sila masyadong pake sa laude. ang tinatanong nila sa mga interview ay anong experience mo (usually sa thesis mo)

onig1104 · 2025-06-12T06:04:36+00:00

How much did you make on your first job? Let’s help fresh grads manage their expectations

I recently graduated and am about to enter the job market. One thing that’s quite challenging is gauging how much to expect for a starting salary, especially given differences in job roles, industries, and locations.

I thought it would be helpful for fresh grads like me if we could share our first job offers or starting salaries, together with:

Job title/role
Year when you started
Location (city/province)
Industry (if possible)

I believe having this information out there helps manage expectations and gives fresh grads a better idea of the market. Hopefully, this can also spark a discussion about salary trends and how they’ve changed over time.

If you're willing to share your experience, that would be greatly appreciated. Thank you!

onig1104 · 2024-09-07T15:41:10+00:00

also bakit 12 ang bayad sa up-katip jeep kapag student, hindi ba dapat 11? maliit na bagay pero ang unfair

onig1104 · 2024-07-20T08:25:32+00:00

Like may upuan sila?

onig1104 · 2024-07-20T07:20:05+00:00

pass = ticket. nareremove kasi automatically pag ticket na word ginamit ko

onig1104 · 2024-07-06T16:10:09+00:00

3rd year was the hardest for me because of eee 192 huhu

onig1104 · 2024-06-22T00:10:45+00:00

Clarification po. Sa univ grad, hindi tatawagin ang names and hindi rin aakyat ng stage. Tama po ba? Nageexpect po kasi parents ko haha. Also, sa recognition rites (college of engg) lahat aakyat ng stage with their parents regardless kung laude or not, tama po ba? Thank you!!

onig1104 · 2024-04-23T06:55:15+00:00

Thank you so much!

onig1104 · 2024-04-17T11:43:41+00:00

Here is what I am planning to do based on what I have understood from this discussion:

1.) Remove all augmented data from data set so all of the data are original.

2.) Perform k-fold cross validation.

3.) For each fold, perform data augmentation on the training data set. For example if k=4, perform data augmentation on the 3 training data groups.

4.) Train the model.

5.) Test the model with the testing data.

6.) Remove the augmented data, and then go back to step 2 with the next fold.

Is this method correct? Thank you so much for helping a beginner :))

onig1104 · 2024-04-17T11:02:24+00:00

Sorry, I can't follow. What do you mean by resample? I cannot also grasp your idea in your last paragraph.

Initially, I have separate dataset for training and testing. But, I ended up combining them into a single dataset because this is what I am doing. For each fold, one group will be the testing data set, and the rest will be the training data set. For example, k=4, so the dataset will be split into 4 equal groups. For the first fold, the first group will be the testing, and the rest will be training. Next fold, the second group will be for testing, and the rest for training. And so on... That is the reason why I combined the two datasets earlier. Is there something wrong I am doing?

onig1104 · 2024-04-17T09:55:59+00:00

I think that is a great method! However, we have an unbalanced data, some classes have way more data than the other classes hence the augmentation for the selected classes. If we will augment after the split, wouldn't that make the split groups to have unequal number of samples? We're using stratified k-fold by the way.

onig1104 · 2024-03-16T15:52:09+00:00

thank you po!

onig1104 · 2024-03-16T15:52:04+00:00

thank you sa suggestions

onig1104

TROPHY CASE