Gabriele

My absolutely most hated Error when using python. Similar to C's Segmentation fault (core dumped).

Day 52: Turns out my loss term wasn't differentiable. Thanks goes out to my amazing PhD team for spotting it! #100DaysOfCode

Day 53: Fundus images didn't work, so I will get into enface OCT - using some slabs. Hence, I will get into layer segmentation next!! #100DaysOfCode

Day 51: Looking at my neural network layers with deep dream! #100DaysOfCode

Love your journey!

Day 50: Dataloader for Kandinsky patterns is done! Now I need to find a loss term that makes my network not only sparse but also modular! So in love with my PhD team, they help me verbalise my problems 🤓 #100DaysOfCode

Day 49: Meeting with my Doctoral supervisor and advisors was fun as always! Great new ideas for how to proceed - mainly dataset and loss term related. #100DaysOfCode

Day 48: Optimisation of graph visualisation in 3D!! (currently not working) #100DaysOfCode

Day 47: Doing some optimisation. It's working! at least in a small scale! #100DaysOfCode

Day 46: Goal to get all of the umap plots look similar: failed. Tried with transform once, fit multiple times. Maybe the amount of datapoints is the problem. Keep going, keep growing! #100DaysOfCode

Day 45: Yesterday, I tried to further understand my data. The labels don't make too much sense to me, hence messaged a clinician! #100DaysOfCode

Day 44: Plotting data for genes related to AMD. Super excited to feed a neutral network with it combined with images 😍 #100DaysOfCode

Day 42: Yesterday I was trying to implement a dataloader and for whatever magic reason it's not working. #100DaysOfCode

Day 42: Suddenly everything stopped working ... #100DaysOfCode

Day 43: Music to my ears (or to my laptops ears) - new cuda version after 4 years! #100DaysOfCode

Day 31: Searching for some benchmarking datasets and metrics! #100DaysOfCode

Error messages and way too high loss values.

Day 32: I promise, I am an expert in deep learning. #100DaysOfCode

Python/Matplotlib, showing (bad) prediction results.

Day 33: Clearly not working. Still, I made progress with understanding LSTM. #100DaysOfCode

Day 34: Made progress on my code today thanks to @mateosuffern.bsky.social! Turning some pytorch code into pytorch lightning. My favourite part are the sanity checks! #100DaysOfCode

Day 35: Lots of modularity and honey bee colony loss write-up! #100DaysOfCode

and the actual update - trying to translate pytorch into torch lightning!

Day 36: My torch lightning attempts to gracefully shut down! Maybe I should do the same with my coding career. [joke] #100DaysOfCode

Saw my first ever and second rocket launches in the past 24h!!! Super amazing experience, and the sunrise was the cherry on top 😭😍

Day 37: Baseline testing! #100DaysOfCode

TabPFN Code

Secondly, I have been dissecting some scikit-model code.

Python Error Message

Day 38: Two things today!! Number one - problems with dimensions for the metrics. Have to translate them back from one-hot I guess. #100DaysOfCode

Model training

Day 39: All bugs fixed! (this will probably jinx it, but oh well). Model is training! #100DaysOfCode

Day 40: More coding for modular training!! #100DaysOfCode

Python code

Day 41: Another day of #100DaysOfCode! I fixed a problem with gradients. Really just switched to manual optimisation in PyTorch lightning, which resulted in the need of changing the callback for saving checkpoints. Seems to work now. Next thing - troubleshooting the visualisation (I don't trust).

Some cool prof in eye research just asked me what I published. Well, there is this project on an idea for a mission to Neptune in a journal. I have a feeling he wanted another answer 👀 but well, I do what I can 😂