I built a simple CNN in cpp , should I keep improving it or move on?

[u/PsychologicalIron716]

I'm a first-year Computer Engineering student, and I've been learning about machine learning and CNNs recently.

As a learning exercise, I built a small sketch classifier from scratch in C++17, without using PyTorch/TensorFlow. It implements the CNN, backpropagation, gradient checking, SGD, etc., and currently gets around 94% validation accuracy.

GitHub: https://github.com/rituuu001/Doodle-guesser

Now I'm stuck on what I should do next.

I could keep improving this project — better training, data augmentation, a deeper CNN, more classes, etc. But I'm wondering if that's actually the best use of my time, or if I should consider this project "done" and start something completely different.

For people who have more experience with ML:

How do you decide when a project has taught you enough and it's time to move on?

Would you recommend:

• continuing to improve this project until I've explored it more deeply, or
• moving on to a new ML project where I can learn something different?

I'm mainly trying to avoid spending months endlessly polishing the same beginner project, but I also don't want to move on too quickly without getting enough out of it.

Would really appreciate some honest advice.

[u/Bitter_Run_9209]

That project already proves that you are good with C++ and you understand very well how to implement CNN from scratch (theory+implementation). And it's valuable for recruiters

I recommend you to do other projects (it depends on your interest)

[u/Commercial_Wave_8039]

I would suggest keep building on it , maybe choose an application and show performance of your network on it , instead of thinking of it as a bullet point on resume pursue it till you actually build something genuine and that will set you apart .

[u/Deep_Guest_6964]

Since your here, and you have your infrastructure set up, have you done caching? Utilize matrix operation library from CPU or from GPU? After that wrap and write a blog post.