Hello everyone!
I previously worked on the alligator vs crocodile app. Here on top of which @Lankinen wrote an amazing post and article Even though it was working fine but I was not satisfied with the testing results. So I decided to make version2 of the app (again focusing on Deep learning part. I am not a UI person). So I collected around 4k images (2k crocodile and 2k alligators) and trained my model with close to 97% accuracy. After that I deployed it on Heroku. You can find the app in action here. Interesting that this problem of classifying them is harder than I expected.
What is interesting is, I put my both models weights. V1 for previous weights and epoch 36 and epoch 72 for V2 model. I ran my model on all test images and saved the results in database provided by the Heroku itself. I saved images and now at the end of each day, I am resetting counts and fine-tuning model. (Someone asked the exact same question in today’s class). I am planning to do that weekly instead of daily. I have a medium post write-up Still a draft
You can check the current by appending /check_counts in front of URL. Check counts of the model.
This is a really learning experience for me. I deployed a Heroku app with heroku database in a docker container and trained 2 different models. Learned a lot.
Thanks