17. Forgot to kill my process… sorry team! 36. “Quick 5-min sync” = 45 minutes 38. Nice pajama top on the call 19. Server rebooted overnight. RIP my results. 31. Wait… which cell did I run last? 32. Jupyter kernel died mysteriously 23. Dataset has 47 samples. Total. 15. Someone hogged all GPUs 1. Can we get 99.9% accuracy? 24. The data is too noisy to use 7. This should be simple, right? 29. Works perfectly on my machine 10. When will the model be production- ready? 3. A meeting could have been an email 18. SSH connection died mid- experiment 9. The business need has… evolved 35. As per my last email… 20. We need more data 11. Who left training running ALL weekend? Free! 13. CUDA out of memory 4. Requirements changed… again 28. Loss went to NaN on step 1 21. The labels are completely wrong 8. Just add ONE more feature before launch 40. Internet died at demo time 2. Actually, let’s pivot the entire approach 27. Ground truth isn’t actually true 14. The server is suspiciously slow today 39. Pet photobombed the video call 22. Who annotated this?! 30. Forgot to shuffle the dataset 6. Stakeholder ghosted after week 2 34. This notebook is 2000 cells long 12. Server crashed during the live demo 33. Restart kernel, run all, pray 5. Can we make it real-time? 26. Test data leaked into training set 25. Extreme class imbalance strikes again 16. OOM killed at epoch 99 of 100 37. I’ll document this later 17. Forgot to kill my process… sorry team! 36. “Quick 5-min sync” = 45 minutes 38. Nice pajama top on the call 19. Server rebooted overnight. RIP my results. 31. Wait… which cell did I run last? 32. Jupyter kernel died mysteriously 23. Dataset has 47 samples. Total. 15. Someone hogged all GPUs 1. Can we get 99.9% accuracy? 24. The data is too noisy to use 7. This should be simple, right? 29. Works perfectly on my machine 10. When will the model be production- ready? 3. A meeting could have been an email 18. SSH connection died mid- experiment 9. The business need has… evolved 35. As per my last email… 20. We need more data 11. Who left training running ALL weekend? Free! 13. CUDA out of memory 4. Requirements changed… again 28. Loss went to NaN on step 1 21. The labels are completely wrong 8. Just add ONE more feature before launch 40. Internet died at demo time 2. Actually, let’s pivot the entire approach 27. Ground truth isn’t actually true 14. The server is suspiciously slow today 39. Pet photobombed the video call 22. Who annotated this?! 30. Forgot to shuffle the dataset 6. Stakeholder ghosted after week 2 34. This notebook is 2000 cells long 12. Server crashed during the live demo 33. Restart kernel, run all, pray 5. Can we make it real-time? 26. Test data leaked into training set 25. Extreme class imbalance strikes again 16. OOM killed at epoch 99 of 100 37. I’ll document this later
(Print)
17. Forgot to kill my process… sorry team!
36. “Quick 5-min sync” = 45 minutes
38. Nice pajama top on the call
19. Server rebooted overnight. RIP my results.
31. Wait… which cell did I run last?
32. Jupyter kernel died mysteriously
23. Dataset has 47 samples. Total.
15. Someone hogged all GPUs
1. Can we get 99.9% accuracy?
24. The data is too noisy to use
7. This should be simple, right?
29. Works perfectly on my machine
10. When will the model be production-ready?
3. A meeting could have been an email
18. SSH connection died mid-experiment
9. The business need has… evolved
35. As per my last email…
20. We need more data
11. Who left training running ALL weekend?
Free!
13. CUDA out of memory
4. Requirements changed… again
28. Loss went to NaN on step 1
21. The labels are completely wrong
8. Just add ONE more feature before launch
40. Internet died at demo time
2. Actually, let’s pivot the entire approach
27. Ground truth isn’t actually true
14. The server is suspiciously slow today
39. Pet photobombed the video call
22. Who annotated this?!
30. Forgot to shuffle the dataset
6. Stakeholder ghosted after week 2
34. This notebook is 2000 cells long
12. Server crashed during the live demo
33. Restart kernel, run all, pray
5. Can we make it real-time?
26. Test data leaked into training set
25. Extreme class imbalance strikes again
16. OOM killed at epoch 99 of 100
37. I’ll document this later
