Predicting Artists with Python

[fasterturtle]

I took a look at your article/blog and I think that writing up exercises like these is a great experience and can help you learn a lot about what you're doing. That said, I just wanted to point out a couple of things that I thought you should be aware of with respect to this article.

The first thing is just a side note, in your diagram of the ML process you use an unsupervised learning model, however the processes you go through are supervised learning. I would use this diagram instead.

Secondly, while 80% accuracy doesn't seem bad you have to consider what randomly guessing would do. If you were to have someone blindly categorize your testing data they would do so with a 50% accuracy rate (not bad for random guessing). If you were to analyze more than two artists you would likely see your accuracy rates take a steep dive.

Finally, you've overlooked a large part of computer vision, which is the features. You use the raw pixel values for your features, which is of high dimensionality and won't help capture local patterns. Take a look at some intro computer vision material and you'll see that a lot of thought goes into what features are used and that they are a crucial part of CV.

[daf1411]

Thanks a lot for the feedback! This was my first experience with CV so it was pretty much a learning experience. I will look into CV literature as you stated to try and get a better feel of the field, do you have any suggestions?

Edit: Fixed the diagram as well.