Recently I took part in a little competition to write a simple machine learning model, which should be able to classify about 120 different fruits.
Since the data itself is very beginner-friendly and I have to very little to none data cleaning work, the whole process was tent to exploring data and picking hyperparameters.
After approximately 7 hours of coding and waiting my (partly pretrained) model was finished I get some really interesting results. Following are some of its output of the network for a set of selected images.
I will also include some photos of how the data is processed during the process of prediction.
The network structure itself is not an impressive work since I did not invent it myself. But behind the scene, there is a ton of works I put in in order to understand the topic, which is, to be honest, an immense computer science field even if you just go just a little in the depth.