u/Djistino

​

I’m trying to free up space in Google Photos without deleting the original files on my phone.

I created a “NotSynced” folder, turned OFF backup for that folder, and moved (and even copied) the videos I want to keep on my device into it.

But here’s the problem:

- Even if I copy the videos into the NotSynced folder

- And turn off “Back up & sync” for that folder

- When I delete the video from Google Photos (Move to Trash),

the copy in my device folder also gets deleted.

- When I restore it from trash, it comes back into both folders again.

Why is Google Photos deleting files from my device even when the folder isn't backed up?

Is there any simple way to delete photos/videos from Google Photos without deleting the local copy from my phone?

I tried making a separate folder, moving files, copying files, turning off backup for that folder — nothing stops Google Photos from deleting the device copy.

Any fix for this?

So the problem is that my teacher posted a machine learning " Time series classification problem" and what i did is that instead of making my best public score better by coding which was 0.85 , i did search for the data set which i did find it and i made the sub file based on it and it got me 1.00 now is there a way to make the code based on this data i did submit it , like is there a way to know how to make the sub file only by the train and test files idk if i can call it a reverse engineering the sub file

I would really appreciate your help help and if u want me to share the train/test or the sub file that got me the 1.00 score just leave a comment and thanks for the help

My teacher gave us a machine learning time series classification problem.

At first, I tried solving it normally and got a public score of 0.85. But then I searched for the dataset used in the competition and managed to find it. Using that dataset, I generated a submission file that scored 1.00.

Now my question is:

Is it possible to recreate the submission file using only the provided train and test datasets, without relying on the external dataset I found?

In other words, I want to understand if there is a way to learn or reverse-engineer how to produce the same submission output (ID → label mapping) using only the original train/test files. I’m not sure if “reverse engineering the submission” is the correct term, but I want to figure out how to get the same result properly using machine learning rather than external data.

Also, I want to clarify that for the submission I made, I actually had access to the full feature set—not just IDs and labels, meaning the other feature of the sub file

I would really appreciate any help or guidance. If needed, I can share the train/test files or the submission file that achieved the 1.00 score.

Thanks in advance!