Two years ago, I had a need to detect if an image was upside down or right-side up. It occurred to me that this seems like a binary classification problem so I

Two years ago, I had a need to detect if an image was upside down or right-side up. It occurred to me that this seems like a binary classification problem so I went through the whole process of building a model from scratch, downloading data, feeding it in, optimizing the model, optimizing the data, and so on and so forth. The final result is here: https://github.com/kevmo314/image-orientation-detection https://github.com/kevmo314/image-orientation-detection The repo itself is probably not that insightful because it was the actual steps that taught me a lot but finding a problem that I felt like was independently solvable and then solving it with a neural net helped me go from only an academic knowledge of neural networks to being able to confidently implement them. I can highly recommend trying to find a similar problem (one that isn't just "someone on the internet suggested I do this as an exercise") if that resonates with you since it was going from the feeling of not knowing that it could be done to a final model that taught me the most. Also, if you're curious, the use case was I needed was a way to detect if video coming from a GoPro was upside down.